2008
51.
Ewa Niewiadomska-Szynkiewicz, Agnieszka Zawadzka
Integrated Software Platform for Parallel Global Optimization Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 147-156, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.16,
title = {Integrated Software Platform for Parallel Global Optimization},
author = {Ewa Niewiadomska-Szynkiewicz and Agnieszka Zawadzka},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.16.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {147-156},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {The paper is concerned with global optimization techniques and their parallel implementation. We describe an integrated software platform GOOL–PV (Global Optimization Object-oriented Library–Parallel Version) that provides the tools for solving complex optimization problems on parallel and multi-core computers or computer clusters. Finally, we present the comparative study of sequential and parallel global optimization algorithms based on numerical results for a standard set of multimodal functions.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper is concerned with global optimization techniques and their parallel implementation. We describe an integrated software platform GOOL–PV (Global Optimization Object-oriented Library–Parallel Version) that provides the tools for solving complex optimization problems on parallel and multi-core computers or computer clusters. Finally, we present the comparative study of sequential and parallel global optimization algorithms based on numerical results for a standard set of multimodal functions.
52.
Robert Nowak, Marcin Romaniuk
Long DNA Strands Synthesis Optimizing Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 157-164, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.17,
title = {Long DNA Strands Synthesis Optimizing},
author = {Robert Nowak and Marcin Romaniuk},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.17.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {157-164},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {The method described in this paper helps to syntheses DNA (deoxyribonucleic acid) molecules with length about 1000 bp, using typical techniques enable to create strands of length up to 70 bp. The given DNA strand is divided into smaller fragments, and next these fragments are connected by proposed protocol in genetic laboratory. The evolutionary algorithm is used to find the optimal solution. The freely accessible application called longdna, based on presented ideas was implemented and tested on simulated and real data.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The method described in this paper helps to syntheses DNA (deoxyribonucleic acid) molecules with length about 1000 bp, using typical techniques enable to create strands of length up to 70 bp. The given DNA strand is divided into smaller fragments, and next these fragments are connected by proposed protocol in genetic laboratory. The evolutionary algorithm is used to find the optimal solution. The freely accessible application called longdna, based on presented ideas was implemented and tested on simulated and real data.
53.
Przemysław Kobylański
Modeling Fuzzy Intervals With Constraint Logic Programming Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 9-22, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.1,
title = {Modeling Fuzzy Intervals With Constraint Logic Programming},
author = {Przemysław Kobylański},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.1.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {9-22},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {In this paper the method of modeling fuzzy intervals in fuzzy decisionmaking is presented. Described method makes use of constraint logic programming and it is based on the concept of descriptors. This approach is very general and it is consistent with Zadehtextquoterights extension principle and Bellman-Zadeh concept of fuzzy decision making. It fulfills Klirtextquoterights requisite constraint and deals effectively with a drowning effect too. The idea of descriptors of fuzzy intervals and fuzzy constraints is illustrated with computational example of flexible scheduling problem in which robust for drowning effect schedule is found.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper the method of modeling fuzzy intervals in fuzzy decisionmaking is presented. Described method makes use of constraint logic programming and it is based on the concept of descriptors. This approach is very general and it is consistent with Zadehtextquoterights extension principle and Bellman-Zadeh concept of fuzzy decision making. It fulfills Klirtextquoterights requisite constraint and deals effectively with a drowning effect too. The idea of descriptors of fuzzy intervals and fuzzy constraints is illustrated with computational example of flexible scheduling problem in which robust for drowning effect schedule is found.
54.
Jan J. Mulawka
A Molecular Inference via Colorimetric Change Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 139-146, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.15,
title = {A Molecular Inference via Colorimetric Change},
author = {Jan J. Mulawka},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.15.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {139-146},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {In this work the inference performed on DNA molecules is considered.The process known as self-assembling of DNA strands is fundamental to achieve longer chains of molecules encoding knowledge base. By proper organization of this process any logic operations can be accomplished. In particular, systems based on decision trees may be easy assembled. A severe problem of nano-systems is to provide communication between nano-world and real-world. To solve this problem it is proposed to make use of colorimetric change phenomenon. Here an inference procedure is proposed that allows to check the knowledge base in form of decision tree. Although DNA strands react in the nano-world, due to optical read-out the inference result is attained quickly and easy. Thus, complicated and expensive operations of genetic engineering laboratory are eliminated.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In this work the inference performed on DNA molecules is considered.The process known as self-assembling of DNA strands is fundamental to achieve longer chains of molecules encoding knowledge base. By proper organization of this process any logic operations can be accomplished. In particular, systems based on decision trees may be easy assembled. A severe problem of nano-systems is to provide communication between nano-world and real-world. To solve this problem it is proposed to make use of colorimetric change phenomenon. Here an inference procedure is proposed that allows to check the knowledge base in form of decision tree. Although DNA strands react in the nano-world, due to optical read-out the inference result is attained quickly and easy. Thus, complicated and expensive operations of genetic engineering laboratory are eliminated.
55.
Piotr Wąsiewicz, Anna Wójtowicz-Krawiec, Andrzej Płucienniczak
Molecular NOR Logic Gate Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 237-244, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.26,
title = {Molecular NOR Logic Gate},
author = {Piotr Wąsiewicz and Anna Wójtowicz-Krawiec and Andrzej Płucienniczak},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.26.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {237-244},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {Molecular computing created for implementing logic systems, solving NP-difficult problems on nanoscale depends on DNA self-assembly abilities and on modifying DNA with the help of enzymes during genetic operations. In the typical DNA computing a sequence of operations executed on DNA molecules in parallel is called an algorithm, which is also determined by a model of DNA chains. This methodology is similar to the soft hardware specialized architecture driven here by heating, cooling and enzymes, especially polymerases used for copying strings. This work presents a unique approach to implementation of OR, NOR logic gates on molecules. It requires the representation of signals by DNA molecules. The presented method allows for constructing logic gates with many inputs and for executing them at the same quantity of elementary operations, regardless of a number of input signals. The NOR gate was implemented with the help of modified polymerase Taq, which stops its activity, when it meets a molecular obstacle on its way. The appropriate experiment was conducted to confirm the possibilities of the suggested implementation. Laboratory results were discussed.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
Molecular computing created for implementing logic systems, solving NP-difficult problems on nanoscale depends on DNA self-assembly abilities and on modifying DNA with the help of enzymes during genetic operations. In the typical DNA computing a sequence of operations executed on DNA molecules in parallel is called an algorithm, which is also determined by a model of DNA chains. This methodology is similar to the soft hardware specialized architecture driven here by heating, cooling and enzymes, especially polymerases used for copying strings. This work presents a unique approach to implementation of OR, NOR logic gates on molecules. It requires the representation of signals by DNA molecules. The presented method allows for constructing logic gates with many inputs and for executing them at the same quantity of elementary operations, regardless of a number of input signals. The NOR gate was implemented with the help of modified polymerase Taq, which stops its activity, when it meets a molecular obstacle on its way. The appropriate experiment was conducted to confirm the possibilities of the suggested implementation. Laboratory results were discussed.
56.
Robert Sawko, Grzegorz Skorupa
A New Approach to Global Optimization: Sheep Optimization Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 181-188, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.20,
title = {A New Approach to Global Optimization: Sheep Optimization},
author = {Robert Sawko and Grzegorz Skorupa},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.20.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {181-188},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {The paper presents a new meta-heuristics for solving continuous optimization problems of finding a global optimum. The algorithm is based on the behavior of a specific animal species. The main inspiration for this method was a flock of sheep, which after consuming the grass in a certain area, starts to search for new sources of food when the local sources are depleted. A special penalty function to enforce that kind of behavior is proposed. The penalty function together with a gradient-based optimization algorithm became a mechanism for avoiding local maximums and for more thorough exploration of the set of feasible solutions. The comparison with the basic genetic algorithm is presented.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper presents a new meta-heuristics for solving continuous optimization problems of finding a global optimum. The algorithm is based on the behavior of a specific animal species. The main inspiration for this method was a flock of sheep, which after consuming the grass in a certain area, starts to search for new sources of food when the local sources are depleted. A special penalty function to enforce that kind of behavior is proposed. The penalty function together with a gradient-based optimization algorithm became a mechanism for avoiding local maximums and for more thorough exploration of the set of feasible solutions. The comparison with the basic genetic algorithm is presented.
57.
Przemysław Miazga
Simulation-Based Optimization – Myths and Reality Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 131-138, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.14,
title = {Simulation-Based Optimization – Myths and Reality},
author = {Przemysław Miazga},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.14.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {131-138},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {The present paper discusses the influence of simulation model accuracy on the convergence of electromagnetic structure simulation-based optimization. Neither response surface approximation method nor the algorithm of moving window filtering, commonly used for simulation error compensation, is not fully capable of guaranteeing proper convergence. The non-expensive device model with coarse meshing and a modified error compensation method can yield satisfactory results in a reasonable time.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The present paper discusses the influence of simulation model accuracy on the convergence of electromagnetic structure simulation-based optimization. Neither response surface approximation method nor the algorithm of moving window filtering, commonly used for simulation error compensation, is not fully capable of guaranteeing proper convergence. The non-expensive device model with coarse meshing and a modified error compensation method can yield satisfactory results in a reasonable time.
58.
Artur Stasikowski, Tomasz Gwizdałła
Some New Methods in the Evolutionary Search of Atomic Cluster Shape Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 213-220, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.23,
title = {Some New Methods in the Evolutionary Search of Atomic Cluster Shape},
author = {Artur Stasikowski and Tomasz Gwizdałła},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.23.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {213-220},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {The problem of atomic structure optimization related to the minimization of its total energy is a fundamental physical problem as well as hard computational task. For the few last years we have presented some observations concerning the advantages and drawbacks of EA used as a tool to solve such questions. In this paper we would like to present some new approaches devoted to improve the general, not problem oriented part of algorithm. The results obtained for two techniques: population migration and Opposition- Based Learning show that the specific operators, designed for the given problem are still the most important part of algorithm.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The problem of atomic structure optimization related to the minimization of its total energy is a fundamental physical problem as well as hard computational task. For the few last years we have presented some observations concerning the advantages and drawbacks of EA used as a tool to solve such questions. In this paper we would like to present some new approaches devoted to improve the general, not problem oriented part of algorithm. The results obtained for two techniques: population migration and Opposition- Based Learning show that the specific operators, designed for the given problem are still the most important part of algorithm.
59.
Joanna Sztapczyńska, Roman Śmierzchalski
Strength Pareto Evolutionary Approach to Weather Routing – Preliminary Results Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 221-228, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, Augustów, Poland, 2008, ISBN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2008.24,
title = {Strength Pareto Evolutionary Approach to Weather Routing – Preliminary Results},
author = {Joanna Sztapczyńska and Roman Śmierzchalski},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2008.24.pdf},
isbn = {0137-2343},
year = {2008},
date = {2008-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {165},
pages = {221-228},
publisher = {Warsaw University of Technology Publishing House},
address = {Augustów, Poland},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {This paper describes application of Strength Pareto Evolutionary Algorithm (SPEA) to an optimization problem in weather routing. The paper includes a description of SPEA algorithm and defines the constrained weather routing optimization problem. It also presents a proposal and preliminary test results of SPEA-based weather routing evolutionary algorithm.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper describes application of Strength Pareto Evolutionary Algorithm (SPEA) to an optimization problem in weather routing. The paper includes a description of SPEA algorithm and defines the constrained weather routing optimization problem. It also presents a proposal and preliminary test results of SPEA-based weather routing evolutionary algorithm.
2007
60.
Piotr Kwaśniewski, Ewa Niewiadomska-Szynkiewicz
Optimization and control problems in wireless ad hoc networks Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 175-184, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.19,
title = {Optimization and control problems in wireless ad hoc networks},
author = {Piotr Kwaśniewski and Ewa Niewiadomska-Szynkiewicz},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.19.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {175-184},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {Recent advances in technology have enabled the development of low cost, low power and multi functional computation devices. These devices net-worked through wireless bring the idea of mobile ad hoc networks and wireless sensor networks into reality. In this paper we discuss the optimization and control problems related to ad hoc networking topologies and communication. The short description of wireless ad hoc and sensor networks is provided. The focus is on energy conservation techniques and algorithms for computing the optimal transmitting ranges in order to generate a network with desired properties while reducing sensors energy consumption.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
Recent advances in technology have enabled the development of low cost, low power and multi functional computation devices. These devices net-worked through wireless bring the idea of mobile ad hoc networks and wireless sensor networks into reality. In this paper we discuss the optimization and control problems related to ad hoc networking topologies and communication. The short description of wireless ad hoc and sensor networks is provided. The focus is on energy conservation techniques and algorithms for computing the optimal transmitting ranges in order to generate a network with desired properties while reducing sensors energy consumption.
61.
Paweł Czaderna, Konrad Wala
Performance comparison of the AS and GLS algorithms for instance of the weighted maximum leaf spanning tree problem Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 43-50, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.5,
title = {Performance comparison of the AS and GLS algorithms for instance of the weighted maximum leaf spanning tree problem},
author = {Paweł Czaderna and Konrad Wala},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.5.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {43-50},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {In the paper the combinatorial model of the weighted maximum leaf spanning tree problem of simple graph is presented. We give a detailed description of three procedures of the neighbour trees generation to the basis one which are exploited during the course of tree improving process realized by the classical simulated annealing and genetic local search algorithm.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In the paper the combinatorial model of the weighted maximum leaf spanning tree problem of simple graph is presented. We give a detailed description of three procedures of the neighbour trees generation to the basis one which are exploited during the course of tree improving process realized by the classical simulated annealing and genetic local search algorithm.
62.
Andrzej Małolepszy
Predictability of Stock Returns, Using Genetic Programming and Chaos Theory Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 185-192, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.20,
title = {Predictability of Stock Returns, Using Genetic Programming and Chaos Theory},
author = {Andrzej Małolepszy},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.20.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {185-192},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper investigates possibilities of prediction of the Warsaw stock indexes returns, based on the chaos theory. Behavior of the time series, which represent the financial data, is very chaotic. In this paper, the Hurst exponent (H) was used to classify series of financial data, representing different indexes from the Warsaw Stock Exchange. The Hurst exponent may be treated as a measure of predictability. The series with large H, greater than 0.5, can be predicted morę accurately than series with H value close to 0.5. Then, for the selected time series it were reconstructed a higher-dimensional attractor. The values of the delay and the embedding dimension, which are needed to construct the attractor were obtained from auto-mutual information and from the false near neighborstextquoteright method. The time series which contain daily return of indexes were transformed according to a higher-dimensional attractor and prepared as data for a problem of symbolic regression. Genetic programming (GP) was used to generate the functions which match a target curve.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper investigates possibilities of prediction of the Warsaw stock indexes returns, based on the chaos theory. Behavior of the time series, which represent the financial data, is very chaotic. In this paper, the Hurst exponent (H) was used to classify series of financial data, representing different indexes from the Warsaw Stock Exchange. The Hurst exponent may be treated as a measure of predictability. The series with large H, greater than 0.5, can be predicted morę accurately than series with H value close to 0.5. Then, for the selected time series it were reconstructed a higher-dimensional attractor. The values of the delay and the embedding dimension, which are needed to construct the attractor were obtained from auto-mutual information and from the false near neighborstextquoteright method. The time series which contain daily return of indexes were transformed according to a higher-dimensional attractor and prepared as data for a problem of symbolic regression. Genetic programming (GP) was used to generate the functions which match a target curve.
63.
Marcin Suchorzewski, Marcin Korzeń
Programmed death theory revised with artificial evolution Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 269-276, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.30,
title = {Programmed death theory revised with artificial evolution},
author = {Marcin Suchorzewski and Marcin Korzeń},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.30.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {269-276},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {In this paper we revise the Weismanntextquoterights idea of aging and death as adaptive traits. First, we analyze the adaptation process to changing environment of isolated populations (species) having different lifetime and show, that short lifetime may have adaptive value at a population level. Next, we use a Markov chain to model the competition between individuals in a finite population. We derive a condition for equilibrium in the population and explain why the long-lived individuals usually dominate the population. As far as the model reflects reality, our conclusion is that though not impossible, it would require an extraordinary environment for programmed death to be stable adaptive trait.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we revise the Weismanntextquoterights idea of aging and death as adaptive traits. First, we analyze the adaptation process to changing environment of isolated populations (species) having different lifetime and show, that short lifetime may have adaptive value at a population level. Next, we use a Markov chain to model the competition between individuals in a finite population. We derive a condition for equilibrium in the population and explain why the long-lived individuals usually dominate the population. As far as the model reflects reality, our conclusion is that though not impossible, it would require an extraordinary environment for programmed death to be stable adaptive trait.
64.
Małgorzata Gadomska, Andrzej Pacut
Recent Progress in Ant Algorithms for Fixed Telecommunication Networks: A Review Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 79-90, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.9,
title = {Recent Progress in Ant Algorithms for Fixed Telecommunication Networks: A Review},
author = {Małgorzata Gadomska and Andrzej Pacut},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.9.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {79-90},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The aim of this paper is to provide a comprehensive review of Swarm Intelligence based methods for fixed packet-switched telecommunication networks. Such methods, thank to their distributed form and self-organizing dynamics, are very well applicable to problems encountered in a network environment. We believe to show the motivation for using learning methods to solve the routing problem and moreover to create a basis for researchers who act in the field of Swarm Intelligence.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The aim of this paper is to provide a comprehensive review of Swarm Intelligence based methods for fixed packet-switched telecommunication networks. Such methods, thank to their distributed form and self-organizing dynamics, are very well applicable to problems encountered in a network environment. We believe to show the motivation for using learning methods to solve the routing problem and moreover to create a basis for researchers who act in the field of Swarm Intelligence.
65.
Robert Schaefer, Barbara Barabasz, Maciej Paszyński
Twin adaptive scheme for solving inverse problems Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 241-250, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.27,
title = {Twin adaptive scheme for solving inverse problems},
author = {Robert Schaefer and Barbara Barabasz and Maciej Paszyński},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.27.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {241-250},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper deals with a class of inverse parametric problems for which the energy function may be defined. The advanced multi-deme strategy that offers an adaptive accuracy is utilized for solving associated optimal control problems. The direct problems necessary for fitness evaluation are computed by the /ip-adaptive Finite Elements. The new iterative strategy balances the error of solving the direct problem and the error of solving the optimal control problem in order to decrease the total computational cost. The concept of the strategy is partially formally verified (see Lemma 3.1 and 3.2), moreover the advantages in the computational practice are mentioned.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper deals with a class of inverse parametric problems for which the energy function may be defined. The advanced multi-deme strategy that offers an adaptive accuracy is utilized for solving associated optimal control problems. The direct problems necessary for fitness evaluation are computed by the /ip-adaptive Finite Elements. The new iterative strategy balances the error of solving the direct problem and the error of solving the optimal control problem in order to decrease the total computational cost. The concept of the strategy is partially formally verified (see Lemma 3.1 and 3.2), moreover the advantages in the computational practice are mentioned.
66.
Piotr Orantek, Tadeusz Burczyński
The two-stage evolutionary-neuro computing approach for stochastic optimization problems Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 217-224, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.24,
title = {The two-stage evolutionary-neuro computing approach for stochastic optimization problems},
author = {Piotr Orantek and Tadeusz Burczyński},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.24.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {217-224},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {This paper is devoted to the application of the two-stage evolutionary-neuro approach for stochastic optimization problems. The algorithm is based on the stochastic representation of the data. Chromosomes are represented by multidimensional random vectors consisting of random genes in the form of independent random variables with the Gaussian density probability function. The stochastic optimization problem is replaced by deterministic one by evolutionary computing for vector genes consisting of mean values and standard deviations. In the first stage the EA is used. As the second stage in the presented approach the special local gradient method with neuro-computing is proposed.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper is devoted to the application of the two-stage evolutionary-neuro approach for stochastic optimization problems. The algorithm is based on the stochastic representation of the data. Chromosomes are represented by multidimensional random vectors consisting of random genes in the form of independent random variables with the Gaussian density probability function. The stochastic optimization problem is replaced by deterministic one by evolutionary computing for vector genes consisting of mean values and standard deviations. In the first stage the EA is used. As the second stage in the presented approach the special local gradient method with neuro-computing is proposed.
67.
Adam Goinski, Andrzej Obuchowicz
3D Surface Reconstruction by the Means of Evolutionary Algorithms Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 107-114, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.12,
title = {3D Surface Reconstruction by the Means of Evolutionary Algorithms},
author = {Adam Goinski and Andrzej Obuchowicz},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.12.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {107-114},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {In the paper we would like to propose a new method for an isosurface construction from unorganized points in 3-D. The aim is to combine evolutionary algorithms with a recursive subdivision scheme. The algorithm starts from a base population where each individual represents an N-level surface approximation of an input object. Next, the population is evaluated and an offspring generation is created with a denser subdivision of surface. The method is illustrated by a set of samples.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In the paper we would like to propose a new method for an isosurface construction from unorganized points in 3-D. The aim is to combine evolutionary algorithms with a recursive subdivision scheme. The algorithm starts from a base population where each individual represents an N-level surface approximation of an input object. Next, the population is evaluated and an offspring generation is created with a denser subdivision of surface. The method is illustrated by a set of samples.
68.
Roman Galar, Iwona Karcz-Dulęba, Rafał łojek
Adaptation Cost: what is the Repayment Time for the Evolutionary Saddle Crossings? Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 91-98, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.10,
title = {Adaptation Cost: what is the Repayment Time for the Evolutionary Saddle Crossings?},
author = {Roman Galar and Iwona Karcz-Dulęba and Rafał łojek},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.10.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {91-98},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {It is usual to asses alternative optimization search algorithms in terms of the number of trials necessary to approach the optimum. In case of adaptive algorithms implemented in the real systems such assessment seems inadequate, as the loss of quality due to the exploration of the vicinity of the identified optimum should be also taken into account. We try to evaluate this aspect of adaptive search in the case of a path dependent evolution with proportional selection and normally distributed mutations, which involves saddle crossing in a bimodal adaptive landscape.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
It is usual to asses alternative optimization search algorithms in terms of the number of trials necessary to approach the optimum. In case of adaptive algorithms implemented in the real systems such assessment seems inadequate, as the loss of quality due to the exploration of the vicinity of the identified optimum should be also taken into account. We try to evaluate this aspect of adaptive search in the case of a path dependent evolution with proportional selection and normally distributed mutations, which involves saddle crossing in a bimodal adaptive landscape.
69.
Joanna Szlapczynska, Roman Śmierzchalski
An Analysis of MultiObjective Evolutionary Techniques Applicable to Weather Routing Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 277-284, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.31,
title = {An Analysis of MultiObjective Evolutionary Techniques Applicable to Weather Routing},
author = {Joanna Szlapczynska and Roman Śmierzchalski},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.31.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {277-284},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {This document describes possible application of MultiObjective Evolutionary Algorithms (MOEAs) to a problem of finding the most suitable vessel route taking into account changeable weather conditions and several navigational constraints. The paper includes a review of MOEA-specific techniques and presents a proposal of their utilization in a weather routing evolutionary algorithm.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This document describes possible application of MultiObjective Evolutionary Algorithms (MOEAs) to a problem of finding the most suitable vessel route taking into account changeable weather conditions and several navigational constraints. The paper includes a review of MOEA-specific techniques and presents a proposal of their utilization in a weather routing evolutionary algorithm.
70.
Piotr Gawor, Joanna Kołodziej
An Application of Bezier curves in the off-line verification of handwritten signatures Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 99-106, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.11,
title = {An Application of Bezier curves in the off-line verification of handwritten signatures},
author = {Piotr Gawor and Joanna Kołodziej},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.11.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {99-106},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The task of verifying human signatures as a pattern recognition problem is considered in this paper. We propose two-step vectorization procedurę of the binary handwritten signature images with the application of the cubic Bezier curves. We introduce a new contour segments extraction algorithm to generate the discrete sets of signature contour points. A multi-layer neural network trained by the real-coded genetic algorithm was proposed as the signature patterns classifier. Some simple numerical tests results are also reported.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The task of verifying human signatures as a pattern recognition problem is considered in this paper. We propose two-step vectorization procedurę of the binary handwritten signature images with the application of the cubic Bezier curves. We introduce a new contour segments extraction algorithm to generate the discrete sets of signature contour points. A multi-layer neural network trained by the real-coded genetic algorithm was proposed as the signature patterns classifier. Some simple numerical tests results are also reported.
71.
Anna Paszyńska, Maciej Paszyński
An application of hierarchical chromosome based genetic algorithm to the optimization of platform shape. Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 225-232, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.25,
title = {An application of hierarchical chromosome based genetic algorithm to the optimization of platform shape.},
author = {Anna Paszyńska and Maciej Paszyński},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.25.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {225-232},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {In this paper we present hierarchical chromosome based genetic algorithm and its application to solving of exemplary design problem - optimization of platform shape. The problem consists in finding the optimal shape of the platform with minimal overall volume and the stress value not greater then the maximum admissible value, when the platform is under the extremal load. The algorithm uses hierarchical chromosome representation and hierarchical genetic operators, instead of the binary representation and traditional genetic operators. It allows for coding of phenotypes with different number of components as well as performing reproduction with such individuals. In order to solve the problem, the application with hierarchical chromosome based genetic algorithm was interfaced with the parallel fully automatic hp adaptive 3D Finite Element Method package (parhp3D). The parhp3D application was used to compute the stress values for individuals generated by genetic algorithm.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we present hierarchical chromosome based genetic algorithm and its application to solving of exemplary design problem - optimization of platform shape. The problem consists in finding the optimal shape of the platform with minimal overall volume and the stress value not greater then the maximum admissible value, when the platform is under the extremal load. The algorithm uses hierarchical chromosome representation and hierarchical genetic operators, instead of the binary representation and traditional genetic operators. It allows for coding of phenotypes with different number of components as well as performing reproduction with such individuals. In order to solve the problem, the application with hierarchical chromosome based genetic algorithm was interfaced with the parallel fully automatic hp adaptive 3D Finite Element Method package (parhp3D). The parhp3D application was used to compute the stress values for individuals generated by genetic algorithm.
72.
Wojciech Jastrzębski
Application of Hybrid Evolutionary Algorithm to Single Source Capacitated Warehouse Location Problem Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 125-134, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.14,
title = {Application of Hybrid Evolutionary Algorithm to Single Source Capacitated Warehouse Location Problem},
author = {Wojciech Jastrzębski},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.14.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {125-134},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {This paper presents two-phase hybrid evolutionary algorithm (EA) to optimize Single Source Capacitated Warehouse Location Problem (SSCWLP); a well-known location-allocation problem employed for the telecommunication network design modeling. The first phase of the algorithm aims the search to satisfy the problem constraints and during the second phase actual optimization take place. To improve the performance of EA the algorithm is combined with other local search heuristics. Influence of EA hybridization as well as different selection schemes dealing with constraint handling are discussed. In addition, performance of co-evolutionary algorithm (co-EA) versus the EA with single population is compared across a set of example problems.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents two-phase hybrid evolutionary algorithm (EA) to optimize Single Source Capacitated Warehouse Location Problem (SSCWLP); a well-known location-allocation problem employed for the telecommunication network design modeling. The first phase of the algorithm aims the search to satisfy the problem constraints and during the second phase actual optimization take place. To improve the performance of EA the algorithm is combined with other local search heuristics. Influence of EA hybridization as well as different selection schemes dealing with constraint handling are discussed. In addition, performance of co-evolutionary algorithm (co-EA) versus the EA with single population is compared across a set of example problems.
73.
Ewa Figielska
Combining a Genetic Algorithm With a Column Generation Algorithm for Solving a Scheduling Problem Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 71-78, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.8,
title = {Combining a Genetic Algorithm With a Column Generation Algorithm for Solving a Scheduling Problem},
author = {Ewa Figielska},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.8.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {71-78},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {This paper deals with the problem of minimal makespan scheduling in a two-stage flowshop with parallel unrelated machines and renewable resources at the first stage and a single machinę at the second stage. A heuristic for solving this problem is developed which combines a genetic algorithm with a column generation algorithm starting from a good feasible solution provided by a fast approximate algorithm. The results of a computational experiment show that the proposed heuristic requires almost three times less CPU time than the heuristic with a standard column generation algorithm, while producing the same quality solutions.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper deals with the problem of minimal makespan scheduling in a two-stage flowshop with parallel unrelated machines and renewable resources at the first stage and a single machinę at the second stage. A heuristic for solving this problem is developed which combines a genetic algorithm with a column generation algorithm starting from a good feasible solution provided by a fast approximate algorithm. The results of a computational experiment show that the proposed heuristic requires almost three times less CPU time than the heuristic with a standard column generation algorithm, while producing the same quality solutions.
74.
Michał Bereta, Tadeusz Burczyński
Combining Negative Selection with Immune K-Means Algorithm for Improving the Support Vector Machines Method Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 25-34, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.3,
title = {Combining Negative Selection with Immune K-Means Algorithm for Improving the Support Vector Machines Method},
author = {Michał Bereta and Tadeusz Burczyński},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.3.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {25-34},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {This paper presents a novel method of using the ideas from Artificial Immune Systems for improving the performance of the Support Vector Machines technique. By means of Immune K-Means algorithm a set of artificial data is generated based on the original training data. The artificial data has the ability to remember the most important information from the classifiers learning point of view - the information about the boundaries among the classes remain in the artificial data. Combining the Immune K-Means algorithm with Negative Selection methods allows for further improvements of the artificial data set. The proposed approach allows to speed up the learning process of SVM when the training data set is large by extracting the most important information first. The proposed methods can also be used as a data compression method especially suited when the information about boundaries among classes is an important issue. The artificial data can be created once and then used for parameters tuning of different classification methods, speeding up the learning process.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents a novel method of using the ideas from Artificial Immune Systems for improving the performance of the Support Vector Machines technique. By means of Immune K-Means algorithm a set of artificial data is generated based on the original training data. The artificial data has the ability to remember the most important information from the classifiers learning point of view - the information about the boundaries among the classes remain in the artificial data. Combining the Immune K-Means algorithm with Negative Selection methods allows for further improvements of the artificial data set. The proposed approach allows to speed up the learning process of SVM when the training data set is large by extracting the most important information first. The proposed methods can also be used as a data compression method especially suited when the information about boundaries among classes is an important issue. The artificial data can be created once and then used for parameters tuning of different classification methods, speeding up the learning process.
75.
Bartłomiej Jacek Kubica, Wojciech Szynkiewicz
CuikSLAM with unknown correspondence -preliminary results Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 153-164, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.17,
title = {CuikSLAM with unknown correspondence -preliminary results},
author = {Bartłomiej Jacek Kubica and Wojciech Szynkiewicz},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.17.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {153-164},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {This paper considers the problem of simultaneous localization and mapping of a mobile robot. The kinematic approach of CuikSLAM is adopted applying constrained satisfaction and interval methods. The novelty is that we do not assume the landmark identification problem to be solved.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper considers the problem of simultaneous localization and mapping of a mobile robot. The kinematic approach of CuikSLAM is adopted applying constrained satisfaction and interval methods. The novelty is that we do not assume the landmark identification problem to be solved.
76.
Rafał Biedrzycki
DNA sequence analysis Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 35-42, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.4,
title = {DNA sequence analysis},
author = {Rafał Biedrzycki},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.4.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {35-42},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {This paper presents a brief survey of computational approaches to the DNA sequence analysis. The basie biological background is presented. The various types of algorithms for pattern construction and gene finding are presented with special attention paid to the application of global optimization methods.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents a brief survey of computational approaches to the DNA sequence analysis. The basie biological background is presented. The various types of algorithms for pattern construction and gene finding are presented with special attention paid to the application of global optimization methods.
77.
Andrzej Obuchowicz
Evolutionary Algorithms with Mutations based on alpha-Stable and Directional Distributions Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 209-216, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.23,
title = {Evolutionary Algorithms with Mutations based on alpha-Stable and Directional Distributions},
author = {Andrzej Obuchowicz},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.23.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {209-216},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {In this paper, a concept of directional mutations for phenotypic evolutionary algorithms is presented. The proposed approach allows, in a very convenient way, to adapt the probability measure underlying the mutation operator during evolutionary process. Simulated experiments confirms the thesis that protextlnotposed mutation improves the effectiveness of evolutionary algorithms in the case of the local as well as global optimization problems.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, a concept of directional mutations for phenotypic evolutionary algorithms is presented. The proposed approach allows, in a very convenient way, to adapt the probability measure underlying the mutation operator during evolutionary process. Simulated experiments confirms the thesis that protextlnotposed mutation improves the effectiveness of evolutionary algorithms in the case of the local as well as global optimization problems.
78.
Witold Beluch, Tadeusz Burczyński, Piotr Orantek
Evolutionary Identification of Fuzzy Materiał Constants in Laminates Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 17-24, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.2,
title = {Evolutionary Identification of Fuzzy Materiał Constants in Laminates},
author = {Witold Beluch and Tadeusz Burczyński and Piotr Orantek},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.2.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {17-24},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper deals with the identification of materiał constants in fibre-reinforced laminates. The Evolutionary Algorithm is used as the global optimization method. The gradient method supported by the Artificial Neural Network is used as the local optimization method. Materiał constants are presented in the form of fuzzy numbers to model their uncertainty. Two types of laminates are considered: simple and hybrid ones. Modal analysis methods are used to collect data necessary for the identification process. The Finite Element Method in fuzzy version is used to solve the direct problem for the laminates. Numerical examples are attached.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper deals with the identification of materiał constants in fibre-reinforced laminates. The Evolutionary Algorithm is used as the global optimization method. The gradient method supported by the Artificial Neural Network is used as the local optimization method. Materiał constants are presented in the form of fuzzy numbers to model their uncertainty. Two types of laminates are considered: simple and hybrid ones. Modal analysis methods are used to collect data necessary for the identification process. The Finite Element Method in fuzzy version is used to solve the direct problem for the laminates. Numerical examples are attached.
79.
Halina Kwaśnicka
Evolving Feedforward Neural Networks – an outcome of simulation studies Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 165-174, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.18,
title = {Evolving Feedforward Neural Networks – an outcome of simulation studies},
author = {Halina Kwaśnicka},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.18.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {165-174},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper is designed as a summary of the relatively wide study on usage of Evolutionary Algorithms (BAs) as an automatic tool for Neural Networks (NNs) design. The study was conducted for many years and partial results have been presented. Special attention is paid to such aspects of NNs evolution as chromosome coding, defining fitness function, and different evolutionary approaches. The studied approaches are shortly described and only generał results, summing up all experiments are presented. Summary contains some recommendations formulated on the basis of experiments. Futurę works are also mentioned.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper is designed as a summary of the relatively wide study on usage of Evolutionary Algorithms (BAs) as an automatic tool for Neural Networks (NNs) design. The study was conducted for many years and partial results have been presented. Special attention is paid to such aspects of NNs evolution as chromosome coding, defining fitness function, and different evolutionary approaches. The studied approaches are shortly described and only generał results, summing up all experiments are presented. Summary contains some recommendations formulated on the basis of experiments. Futurę works are also mentioned.
80.
Michał Marks, Ewa Niewiadomska-Szynkiewicz
Genetic Algorithm and Simulated Annealing Approach to Sensor Network Localization Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 193-202, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.21,
title = {Genetic Algorithm and Simulated Annealing Approach to Sensor Network Localization},
author = {Michał Marks and Ewa Niewiadomska-Szynkiewicz},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.21.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {193-202},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper provides an overview of measurement techniques in sensor networks localization and optimization algorithms based on these measurements for estimation the physical location of nodes with unknown location. A novel localization methods, i.e., two phase algorithms based on simulated annealing and genetic algorithm are described. The numerical results presented and discussed in the finał part of the paper show that these novel schemes give accurate and consistent location estimates of the nodes in the network.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper provides an overview of measurement techniques in sensor networks localization and optimization algorithms based on these measurements for estimation the physical location of nodes with unknown location. A novel localization methods, i.e., two phase algorithms based on simulated annealing and genetic algorithm are described. The numerical results presented and discussed in the finał part of the paper show that these novel schemes give accurate and consistent location estimates of the nodes in the network.
81.
Adam Woźniak
Global Optimization With the Use of Optimal Covering Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 309-316, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.35,
title = {Global Optimization With the Use of Optimal Covering},
author = {Adam Woźniak},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.35.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {309-316},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper describes global optimization algorithm based on Stratified Covering. Stratified means that feasible set is divided into M disjoint subsets of equal volume, and in each subset N sampling points are uniformly generated. Covering concerns method of uniform generation of points and means that sampling grid is the set of centers of N balls, which cover in the finest manner the subset. An abridged description of optimal stratified sampling and optimal covering algorithms containing only the essential of the methods is presented. For the purpose of illustrating both the actual working and the potentialities of the method, a set of computational results is presented.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper describes global optimization algorithm based on Stratified Covering. Stratified means that feasible set is divided into M disjoint subsets of equal volume, and in each subset N sampling points are uniformly generated. Covering concerns method of uniform generation of points and means that sampling grid is the set of centers of N balls, which cover in the finest manner the subset. An abridged description of optimal stratified sampling and optimal covering algorithms containing only the essential of the methods is presented. For the purpose of illustrating both the actual working and the potentialities of the method, a set of computational results is presented.
82.
Łukasz Mirosław, Artur Chorążyczewski
Improved "Aggregated" Model of Evolution Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 203-208, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.22,
title = {Improved "Aggregated" Model of Evolution},
author = {Łukasz Mirosław and Artur Chorążyczewski},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.22.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {203-208},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {We present an improved "aggregated model" where a population is replaced by base point representing population and probe point imitating search process. Presented results shows similar dynamie behavior for proposed algorithm in comparison to model of soft selection algorithms specially for smali populations.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
We present an improved "aggregated model" where a population is replaced by base point representing population and probe point imitating search process. Presented results shows similar dynamie behavior for proposed algorithm in comparison to model of soft selection algorithms specially for smali populations.
83.
Wojciech Jaśkowski, Krzysztof Krawiec, Bartosz Wieloch
Knowledge Reuse for an Ensemble of GP-Based Learners Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 135-142, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.15,
title = {Knowledge Reuse for an Ensemble of GP-Based Learners},
author = {Wojciech Jaśkowski and Krzysztof Krawiec and Bartosz Wieloch},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.15.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {135-142},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {We propose a method of knowledge reuse for an ensemble of genetic programming-based learners solving a visual learning task. First, we introduce a visual learning method that uses genetic programming individuals to repre-sent hypotheses. Individuals-hypotheses process image representation composed of visual primitives derived from given training images that contain objects to be recognized. The process of recognition is generative, i.e., an individual is sup-posed to restore the shape of the processed object by drawing its reproduction on a separate canvas. This canonical method is in the following extended with a knowledge reuse mechanism that allows a learner to import genetic materiał from hypotheses that evolved for other decision classes (object classes). We compare the performance of the extended approach to the basie method on a real-world tasks of handwritten character recognition, and conclude that knowledge reuse leads to significant convergence speedup and reduces the risk of overfitting.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
We propose a method of knowledge reuse for an ensemble of genetic programming-based learners solving a visual learning task. First, we introduce a visual learning method that uses genetic programming individuals to repre-sent hypotheses. Individuals-hypotheses process image representation composed of visual primitives derived from given training images that contain objects to be recognized. The process of recognition is generative, i.e., an individual is sup-posed to restore the shape of the processed object by drawing its reproduction on a separate canvas. This canonical method is in the following extended with a knowledge reuse mechanism that allows a learner to import genetic materiał from hypotheses that evolved for other decision classes (object classes). We compare the performance of the extended approach to the basie method on a real-world tasks of handwritten character recognition, and conclude that knowledge reuse leads to significant convergence speedup and reduces the risk of overfitting.
84.
Piotr Wąsiewicz, Jan J. Mulawka
Lab-on-a-Chip Molecular Inference System Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 293-300, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.33,
title = {Lab-on-a-Chip Molecular Inference System},
author = {Piotr Wąsiewicz and Jan J. Mulawka},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.33.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {293-300},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {Molecular computation on DNA performs calculations using nanotechnology means during chemical reactions. With the help of sili-con industry microfluidic processors were invented utilizing nano membrane valves, pumps and microreactors. These so called lab-on-a-chips combined together with molecular computing create molecular-systems-on-a-chips. This work presents an approach to implementation of logie systems on chips. It requires the unique representation of signals by DNA molecules. The main part of this work includes the concept of logie inference based on typical genetic engineering reactions. The presented method uses a lab-on-a-chip approach. Every microreactor of the lab-on-a-chip performs one unique operation on input molecules and can be connected by dataflow output-input connections to other ones.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
Molecular computation on DNA performs calculations using nanotechnology means during chemical reactions. With the help of sili-con industry microfluidic processors were invented utilizing nano membrane valves, pumps and microreactors. These so called lab-on-a-chips combined together with molecular computing create molecular-systems-on-a-chips. This work presents an approach to implementation of logie systems on chips. It requires the unique representation of signals by DNA molecules. The main part of this work includes the concept of logie inference based on typical genetic engineering reactions. The presented method uses a lab-on-a-chip approach. Every microreactor of the lab-on-a-chip performs one unique operation on input molecules and can be connected by dataflow output-input connections to other ones.
85.
Michał Kudelski, Andrzej Pacut
Learning methods in ad-hoc networks: a review Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 143-152, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.16,
title = {Learning methods in ad-hoc networks: a review},
author = {Michał Kudelski and Andrzej Pacut},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.16.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {143-152},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper presents a comprehensive review of learning methods used to solve various problems in ad-hoc networks. The learning methods are classified according to learning mechanisms and problems solved. Nine representative approaches are discussed in more detail.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper presents a comprehensive review of learning methods used to solve various problems in ad-hoc networks. The learning methods are classified according to learning mechanisms and problems solved. Nine representative approaches are discussed in more detail.
86.
Przemysław Prętki
Learning stable mutation in (1,lambda)ES evolutionary strategy Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 233-240, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.26,
title = {Learning stable mutation in (1,lambda)ES evolutionary strategy},
author = {Przemysław Prętki},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.26.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {233-240},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {In this paper the concept of two-dimensional discrete spectral measure is introduced in the context of its application to real-valued evolutionary strategy (1, X)ES. The notion of discrete spectral measure makes it possible to uniquely define a class of multivariate heavy-tailed distributions, that have received morę and morę attention of evolutionary optimization community, recently. In particular, an adaptation procedurę known from the class of estimation of distribution algorithms (EDAs) is proposed. The effectiveness of the evolutionary strategy is tested by means of a set of popular benchmark functions.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper the concept of two-dimensional discrete spectral measure is introduced in the context of its application to real-valued evolutionary strategy (1, X)ES. The notion of discrete spectral measure makes it possible to uniquely define a class of multivariate heavy-tailed distributions, that have received morę and morę attention of evolutionary optimization community, recently. In particular, an adaptation procedurę known from the class of estimation of distribution algorithms (EDAs) is proposed. The effectiveness of the evolutionary strategy is tested by means of a set of popular benchmark functions.
87.
Tomasz Gwizdałła
Magnetic problems as a benchmark for genetic algorithmtextquoterights operators Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 115-124, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.13,
title = {Magnetic problems as a benchmark for genetic algorithmtextquoterights operators},
author = {Tomasz Gwizdałła},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.13.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {115-124},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {In the paper it is presented the analysis of results and dynamics of evolutionary optimization applied to the well known magnetic Ising model. The data were obtained using different models and genetic operators and allow to formulate some morę generał conclusion concerning the possibilities of solving real NP-hard problems propted by physics.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In the paper it is presented the analysis of results and dynamics of evolutionary optimization applied to the well known magnetic Ising model. The data were obtained using different models and genetic operators and allow to formulate some morę generał conclusion concerning the possibilities of solving real NP-hard problems propted by physics.
88.
Artur Stasikowski, Tomasz Gwizdałła
Modeling of atomic clusters using evolutionary algorithms. Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 261-268, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.29,
title = {Modeling of atomic clusters using evolutionary algorithms.},
author = {Artur Stasikowski and Tomasz Gwizdałła},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.29.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {261-268},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {In the paper there is presented a process of preparation of a tool to geometrical optimization of their total binding energy as well as some physical results. Initially the evolutionary algorithm (EA) was responsible for study of metal clusters described by three-body potential. Afterwards the algorithm was used to perform the exact investigations or rare gas clusters and their modifications by the alkali metal ion doping. The data presented here are the part of PhD dissertation accepted by the Faculty of Physics Uł [1] where are detailed information can be found.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In the paper there is presented a process of preparation of a tool to geometrical optimization of their total binding energy as well as some physical results. Initially the evolutionary algorithm (EA) was responsible for study of metal clusters described by three-body potential. Afterwards the algorithm was used to perform the exact investigations or rare gas clusters and their modifications by the alkali metal ion doping. The data presented here are the part of PhD dissertation accepted by the Faculty of Physics Uł [1] where are detailed information can be found.
89.
Adam Długosz, Tadeusz Burczyński
Multiobjective optimization of heat radiators using evolutionary algorithms Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 51-58, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.6,
title = {Multiobjective optimization of heat radiators using evolutionary algorithms},
author = {Adam Długosz and Tadeusz Burczyński},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.6.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {51-58},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper is devoted to the multiobjective optimization of heat radiators using evolutionary algorithms. The proposed algorithm, based on the Pareto approach, is applied in optimization of heat radiators used to dissipate heat from electrical devices. The boundary-value problem for thermoelasticity is solved using the finite element method. Numerical examples are also included in the paper.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper is devoted to the multiobjective optimization of heat radiators using evolutionary algorithms. The proposed algorithm, based on the Pareto approach, is applied in optimization of heat radiators used to dissipate heat from electrical devices. The boundary-value problem for thermoelasticity is solved using the finite element method. Numerical examples are also included in the paper.
90.
Krzysztof Fabjański, Adam Kozakiewicz, Anna Felkner, Piotr Kijewski, Tomasz Kruk
Multisequence Alignment as a new tool for Network Traffic Analysis Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 59-70, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.7,
title = {Multisequence Alignment as a new tool for Network Traffic Analysis},
author = {Krzysztof Fabjański and Adam Kozakiewicz and Anna Felkner and Piotr Kijewski and Tomasz Kruk},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.7.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {59-70},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {This article presents a multiple sequence alignment as a method used for problems of motif1 finding [13] in network traffic collection. Based on multisequence alignment we will present two bioinformatics approaches for finding longest common subsequence (LCS) [14] of network traffic signatures collection. The article starts from presenting the description of pairwise alignment algorithms, goes through the examples of its implementation and then comes to the part related to bioinformatics methods. At the end, some preliminary results concerning Center Star method will be presented.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This article presents a multiple sequence alignment as a method used for problems of motif1 finding [13] in network traffic collection. Based on multisequence alignment we will present two bioinformatics approaches for finding longest common subsequence (LCS) [14] of network traffic signatures collection. The article starts from presenting the description of pairwise alignment algorithms, goes through the examples of its implementation and then comes to the part related to bioinformatics methods. At the end, some preliminary results concerning Center Star method will be presented.
91.
Anna Witkowska, Roman Śmierzchalski
A New Approach of Genetic Algorithms to Tuning Parameters of Backstepping Ship Course Controller Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 301-308, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.34,
title = {A New Approach of Genetic Algorithms to Tuning Parameters of Backstepping Ship Course Controller},
author = {Anna Witkowska and Roman Śmierzchalski},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.34.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {301-308},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {One of the methods which can be used for designing a nonlinear course controller for ships is the backstepping method. The parameters of the obtained nonlinear control structures were tuned to optimize the operation of the control system. The optimization was performed using genetic algorithms. The quality of operation of the designed control algorithms was checked in simulation tests performed on the mathematical model of the tanker completed by steering gear. The goal of this paper is not to present or propose any new solution in programming of genetic algorithm. It will be rather focused on possibility of use genetic algorithm in backstepping method.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
One of the methods which can be used for designing a nonlinear course controller for ships is the backstepping method. The parameters of the obtained nonlinear control structures were tuned to optimize the operation of the control system. The optimization was performed using genetic algorithms. The quality of operation of the designed control algorithms was checked in simulation tests performed on the mathematical model of the tanker completed by steering gear. The goal of this paper is not to present or propose any new solution in programming of genetic algorithm. It will be rather focused on possibility of use genetic algorithm in backstepping method.
92.
Dariusz Wawrzyniak, Andrzej Obuchowicz
New Evolutionary Algorithm Modifications in Non-stationary Environments Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 285-292, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.32,
title = {New Evolutionary Algorithm Modifications in Non-stationary Environments},
author = {Dariusz Wawrzyniak and Andrzej Obuchowicz},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.32.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {285-292},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {The paper deals with the evolutionary algorithm which uses new methods which allow to increase the efficiency of finding the optimum in an environment in which fitness function is time-varying. Ali methods base on gathering information from environments obtained from the help of individuals (treated as sensors) and use it to help to make a decision to use a particular mechanism. These methods include watching procedurę which provides information about changes in the environment based on using individuals as detectors, multiply rantextlnotdom immigrants mechanism which investigates a particular area of the environment, predict procedurę which tries to calculate the next location of the optimum, memory mechanism which cannot be classified as any existing type of memory.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper deals with the evolutionary algorithm which uses new methods which allow to increase the efficiency of finding the optimum in an environment in which fitness function is time-varying. Ali methods base on gathering information from environments obtained from the help of individuals (treated as sensors) and use it to help to make a decision to use a particular mechanism. These methods include watching procedurę which provides information about changes in the environment based on using individuals as detectors, multiply rantextlnotdom immigrants mechanism which investigates a particular area of the environment, predict procedurę which tries to calculate the next location of the optimum, memory mechanism which cannot be classified as any existing type of memory.
93.
Jarosław Stańczak, Krzysztof Trojanowski
Non-Stationary Optimization with Multi-Population Evolutionary Algorithm Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 251-260, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.28,
title = {Non-Stationary Optimization with Multi-Population Evolutionary Algorithm},
author = {Jarosław Stańczak and Krzysztof Trojanowski},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.28.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {251-260},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {Non-stationary optimization of randomly changing environments is a subject of unfading interest. In this paper we study application of multi-population evolutionary algorithm to this problem. Presented algorithm works with a set of sub-populations managed by the mechanism of exclusion coming from the multiswarm version of particie swarm approach. The results show significant improvement of the efficiency of the new algorithm in comparison with a single population approach.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
Non-stationary optimization of randomly changing environments is a subject of unfading interest. In this paper we study application of multi-population evolutionary algorithm to this problem. Presented algorithm works with a set of sub-populations managed by the mechanism of exclusion coming from the multiswarm version of particie swarm approach. The results show significant improvement of the efficiency of the new algorithm in comparison with a single population approach.
94.
Antanas Zilinskas
On two models for global optimization Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 9-16, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2007, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2007.1,
title = {On two models for global optimization},
author = {Antanas Zilinskas},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2007.1.pdf},
issn = {0137-2343},
year = {2007},
date = {2007-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {160},
pages = {9-16},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe},
abstract = {Two models for global optimization are considered: statistical model, and radial basis functions. The equivalence of both models in the case of optimization without noise is discussed. Both models are also evaluated with respect to global optimization in the presence of noise by means of experimental testing where approximation errors of passive one dimensional algorithm are estimated.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
Two models for global optimization are considered: statistical model, and radial basis functions. The equivalence of both models in the case of optimization without noise is discussed. Both models are also evaluated with respect to global optimization in the presence of noise by means of experimental testing where approximation errors of passive one dimensional algorithm are estimated.
2006
95.
Artur Chorążyczewski, Roman Galar
Adaptive Saddle Crossings in Diverse Landscapes Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 77-85, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2006, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2006.77-85,
title = {Adaptive Saddle Crossings in Diverse Landscapes},
author = {Artur Chorążyczewski and Roman Galar},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2006.77-85.pdf},
issn = {0137-2343},
year = {2006},
date = {2006-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {156},
pages = {77-85},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {There is always a question as to how sound are assessments of evolutionary algorithms capabilities based on the tests made in the specific adaptive landscapes. We present some results of numerical experiments concerning the ability of phenotypic evolution to cross saddles between adaptive peaks of different shapes. Asexual reproduction, proportional selection and normally distributed mutations are used. Some related comments on the benchmarking of evolutionary algorithms are also given.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
There is always a question as to how sound are assessments of evolutionary algorithms capabilities based on the tests made in the specific adaptive landscapes. We present some results of numerical experiments concerning the ability of phenotypic evolution to cross saddles between adaptive peaks of different shapes. Asexual reproduction, proportional selection and normally distributed mutations are used. Some related comments on the benchmarking of evolutionary algorithms are also given.
96.
Jarosław Arabas, Andrzej Dydyński
An Algorithm of Incremental Construction of Nonlinear Parametric Approximators Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 31-38, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2006, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2006.31-38,
title = {An Algorithm of Incremental Construction of Nonlinear Parametric Approximators},
author = {Jarosław Arabas and Andrzej Dydyński},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2006.31-38.pdf},
issn = {0137-2343},
year = {2006},
date = {2006-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {156},
pages = {31-38},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {A novel algorithm of incremental construction of nonlinear parametric approximators is introduced that needs a relatively small number of parameters to achieve good accuracy. The approximator is defined as a linear combination of nonlinear base functions, and the method adds the base functions one by one, observing the correlation between the residue function and the candidate for the base function. The base functions do not need to be homogenous, i.e. to share the same formula. The method was experimentally verified and compared to neural networks, and the preliminary results were encouraging enough to develop the presented approach further.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
A novel algorithm of incremental construction of nonlinear parametric approximators is introduced that needs a relatively small number of parameters to achieve good accuracy. The approximator is defined as a linear combination of nonlinear base functions, and the method adds the base functions one by one, observing the correlation between the residue function and the candidate for the base function. The base functions do not need to be homogenous, i.e. to share the same formula. The method was experimentally verified and compared to neural networks, and the preliminary results were encouraging enough to develop the presented approach further.
97.
Marek Kubiak
Analysis of distance between vehicle routing problem solutions generated by memetic algorithms Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 223-236, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2006, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2006.223-236,
title = {Analysis of distance between vehicle routing problem solutions generated by memetic algorithms},
author = {Marek Kubiak},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2006.223-236.pdf},
issn = {0137-2343},
year = {2006},
date = {2006-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {156},
pages = {223-236},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {This paper focuses on analysis of distance between solutions of the capacitated vehicle routing problem generated by memetic algorihms with different crossover operators. The goal of the analysis is to see what are relative positions of such solutions in search spaces and if different algorithms explore different parts of these spaces. In the described memetic algorithms five different crossover operators are used. The conducted computational experiment shows that solutions generated by the algorithms have very similar, very good quality. From the distance analysis it appears that there are two types of instances of the considered problem: 10 instances have very similar solutions, concentrated in small regions of spaces (textquoterightbig valleystextquoteright), while other 12 have good solutions which reside in different parts of search spaces, implying wide and flat regions of good solutions.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper focuses on analysis of distance between solutions of the capacitated vehicle routing problem generated by memetic algorihms with different crossover operators. The goal of the analysis is to see what are relative positions of such solutions in search spaces and if different algorithms explore different parts of these spaces. In the described memetic algorithms five different crossover operators are used. The conducted computational experiment shows that solutions generated by the algorithms have very similar, very good quality. From the distance analysis it appears that there are two types of instances of the considered problem: 10 instances have very similar solutions, concentrated in small regions of spaces (textquoterightbig valleystextquoteright), while other 12 have good solutions which reside in different parts of search spaces, implying wide and flat regions of good solutions.
98.
Joanna Kołodziej
An Application of Erlang Mixture Distributions to modeling the reproduction mechanism in estimation of distribution algorithms. Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 203-210, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2006, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2006.203-210,
title = {An Application of Erlang Mixture Distributions to modeling the reproduction mechanism in estimation of distribution algorithms.},
author = {Joanna Kołodziej},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2006.203-210.pdf},
issn = {0137-2343},
year = {2006},
date = {2006-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {156},
pages = {203-210},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {We present the idea of an application of the mixtures of Erlang distributions in the construction of the recombination mechanism in estimation of distribution algorithms. We analyze main properties of Erlang mixtures and define a new Erlang Mixture Estimation of Distribution Algorithm. We try to compare the efficiencies of ErM-EDA and evolutionary strategy in case of large populations. Some experimental results are presented after simple theoretical studies.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
We present the idea of an application of the mixtures of Erlang distributions in the construction of the recombination mechanism in estimation of distribution algorithms. We analyze main properties of Erlang mixtures and define a new Erlang Mixture Estimation of Distribution Algorithm. We try to compare the efficiencies of ErM-EDA and evolutionary strategy in case of large populations. Some experimental results are presented after simple theoretical studies.
99.
Jarosław Arabas
Asymptotic Correctness of the Evolutionary Algorithm in Banach Space Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 21-30, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2006, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2006.21-30,
title = {Asymptotic Correctness of the Evolutionary Algorithm in Banach Space},
author = {Jarosław Arabas},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2006.21-30.pdf},
issn = {0137-2343},
year = {2006},
date = {2006-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {156},
pages = {21-30},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {The paper gives two theorems for the asymptotic correctness of an evolutionary algorithm (EA) that processes chromosomes from an arbitrary Banach space. It is argued that even if the mutation cannot yield an arbitrarily far offspring, the EA may be asymptotically correct provided that the selection is nonelitist and each feasible individual may reproduce with nonzero probability. An illustrative example accompanies the paper.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper gives two theorems for the asymptotic correctness of an evolutionary algorithm (EA) that processes chromosomes from an arbitrary Banach space. It is argued that even if the mutation cannot yield an arbitrarily far offspring, the EA may be asymptotically correct provided that the selection is nonelitist and each feasible individual may reproduce with nonzero probability. An illustrative example accompanies the paper.
100.
Eugene Eberbach
Capturing Evolution of Polymorphic Viruses Proceedings Article
In: Arabas, J. (Ed.): Evolutionary Computation and Global Optimization, pp. 125-138, Warsaw University of Technology Publishing House Warsaw University of Technology Publishing House, 2006, ISSN: 0137-2343.
Abstract | Links | BibTeX | Tagi: kaeiog
@inproceedings{KAEiOG2006.125-138,
title = {Capturing Evolution of Polymorphic Viruses},
author = {Eugene Eberbach},
editor = {J. Arabas},
url = {https://troja.uksw.edu.pl/pdf/kaeiog/KAEiOG2006.125-138.pdf},
issn = {0137-2343},
year = {2006},
date = {2006-01-01},
booktitle = {Evolutionary Computation and Global Optimization},
number = {156},
pages = {125-138},
publisher = {Warsaw University of Technology Publishing House},
organization = {Warsaw University of Technology Publishing House},
series = {Prace Naukowe, Elektronika},
abstract = {In this paper three models of polymorphic viruses are presented. These models had to capture self-poduction, evolution and damaging payload of polymorphic viruses. They have been derived using a formal model of Evolutionary Computation the Evolutionary Turing Machine, cellular space models, and the $-calculus process algebra for problem solving. Some preliminary results associated with these models are discussed.},
keywords = {kaeiog},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper three models of polymorphic viruses are presented. These models had to capture self-poduction, evolution and damaging payload of polymorphic viruses. They have been derived using a formal model of Evolutionary Computation the Evolutionary Turing Machine, cellular space models, and the $-calculus process algebra for problem solving. Some preliminary results associated with these models are discussed.