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2018 | OriginalPaper | Chapter

Hybrid Evolutionary System to Solve Optimization Problems

Author : Krzysztof Pytel

Published in: Artificial Intelligence and Soft Computing

Publisher: Springer International Publishing

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Abstract

The article presents an Evolutionary System designed to solve optimization problems. The system consists of Genetic Algorithm and Evolutionary Strategy, working together to improve the efficiency of optimization and increase the resistance to stuck to suboptimal solutions. In the system, we combined the ability of the Genetic Algorithm to explore the search space and the ability of the Evolutionary Strategy to exploit the search space. The system maintains the right balance between the ability to explore and exploit the search space. Genetic Algorithm and Evolutionary Strategy can exchange information about the solutions found till now and periodically migrate the best individuals between populations. The efficiency of the system has been investigated by an example of function optimization. The results of the experiments suggest that the proposed system can be an effective tool in solving complex optimization problems.

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previous chapter Particle Swarm Optimization with Single Particle Repulsivity for Multi-modal Optimization
next chapter Horizontal Gene Transfer as a Method of Increasing Variability in Genetic Algorithms
Literature
1.
Bäck, T., Hoffmeister, F., Schwefel, H.-P.: A survey of evolution strategies. In: Proceedings of the Fourth International Conference on Genetic Algorithms, vol. 2, no. 9. Morgan Kaufmann (1991)
2.
Beyer, H.-G., Schwefel, H.-P.: Evolution strategies: a comprehensive introduction. J. Nat. Comput. 1(1), 3–52 (2002)MathSciNetCrossRef
3.
Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning Reading. Addison-Wesley, Boston (1989)MATH
4.
Jensi, R., Jiji, G.W.: An improved krill herd algorithm with global exploration capability for solving numerical function optimization problems and its application to data clustering. Appl. Soft Comput. 46, 230–245 (2016)CrossRef
5.
6.
Karaboga, D., Basturk, B.: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J. Glob. Optim. 39(3), 459–471 (2007)MathSciNetCrossRef
7.
Kwasnicka, H.: Evolutionary Computation in Artificial Intelligence. Publishing House of the Wroclaw University of Technology, Wroclaw (1999). (in Polish)
8.
9.
10.
Pytel, K.: The fuzzy genetic strategy for multiobjective optimization. In: Proceedings of the Federated Conference on Computer Science and Information Systems, Szczecin (2011)
11.
12.
Pytel, K., Nawarycz, T.: A fuzzy-genetic system for ConFLP problem. In: Advances in Decision Sciences and Future Studies, vol. 2. Progress & Business Publishers, Krakow (2013)
13.
14.
Pytel, K.: Hybrid multievolutionary system to solve function optimization problems. In: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, Prague, Czech Republik (201). https://​doi.​org/​10.​15439/​2017F85
15.
Rutkowska, D.: Intelligent Computational Systems. Academic Publishing House PLJ, Warsaw (1997)
16.
Rutkowska, D., Pilinski, M., Rutkowski, L.: Neural Networks, Genetic Algorithms and Fuzzy Systems. PWN Scientific Publisher, Warsaw (1997)
17.
18.
Metadata
Title
Hybrid Evolutionary System to Solve Optimization Problems
Author
Krzysztof Pytel
Copyright Year
2018
Book
Artificial Intelligence and Soft Computing

Print ISBN: 978-3-319-91252-3

Electronic ISBN: 978-3-319-91253-0

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-91253-0_46

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