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Species co-evolutionary algorithm: a novel evolutionary algorithm based on the ecology and environments for optimization

  • Theory and Applications of Soft Computing Methods
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Abstract

In classic evolutionary algorithms (EAs), solutions communicate each other in a very simple way so the recombination operator design is simple, which is easy in algorithms’ implementation. However, it is not in accord with nature world. In nature, the species have various kinds of relationships and affect each other in many ways. The relationships include competition, predation, parasitism, mutualism and pythogenesis. In this paper, we consider the five relationships between solutions to propose a co-evolutionary algorithm termed species co-evolutionary algorithm (SCEA). In SCEA, five operators are designed to recombine individuals in population. A set including several classical benchmarks are used to test the proposed algorithm. We also employ several other classical EAs in comparisons. The comparison results show that SCEA exhibits an excellent performance to show a huge potential of SCEA in optimization.

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Acknowledgments

This work was sponsored by the National Natural Science Foundation of China under Grant Nos. 61203250, 70871091, 61075064, 61034004 and 61005090, Program for New Century Excellent Talents in University of Ministry of Education of China, Ph.D. Programs Foundation of Ministry of Education of China (20100072110038), Program for Young Excellent Talents in Tongji University (1850219017). We appreciate the work and support in codes from Associate Professor MAO Yanfen who is with Sino-German College of Applied Science, Tongji University, China.

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Authors and Affiliations

  1. Department of Electronics and Information, Tongji University, Shanghai, 201804, China

    Wuzhao Li, Lei Wang & Xingjuan Cai

  2. Sino-German College Applied Sciences of Tongji University, Shanghai, 201804, China

    Weian Guo

  3. Center for Electric Power and Energy, Department of Electrical Engineering, Technical University of Denmark, 2800, Copenhagen, Denmark

    Junjie Hu

  4. Jiaxing Vocational Technical College, Jiaxing, 314036, Zhejiang, China

    Wuzhao Li

Authors
  1. Wuzhao Li
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  2. Lei Wang
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  3. Xingjuan Cai
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  4. Junjie Hu
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  5. Weian Guo
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Corresponding author

Correspondence to Weian Guo.

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Li, W., Wang, L., Cai, X. et al. Species co-evolutionary algorithm: a novel evolutionary algorithm based on the ecology and environments for optimization. Neural Comput & Applic 31, 2015–2024 (2019). https://doi.org/10.1007/s00521-015-1971-3

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  • DOI: https://doi.org/10.1007/s00521-015-1971-3

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