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Hybrid Evolutionary System to Solve Optimization Problems

  • Krzysztof PytelEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10841)

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.

Keywords

Genetic Algorithms Evolutionary Strategies Artificial intelligence Function optimization 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Physics and Applied InformaticsUniversity of LodzŁódźPoland

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