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Implementation of cellular genetic algorithms with two neighborhood structures for single-objective and multi-objective optimization

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Abstract

In cellular algorithms, a single neighborhood structure for local selection is usually assumed to specify a set of neighbors for each cell. There exist, however, a number of examples with two neighborhood structures in nature. One is for local selection for mating, and the other is for local competition such as the fight for water and sunlight among neighboring plants. The aim of this paper is to show several implementations of cellular algorithms with two neighborhood structures for single-objective and multi-objective optimization problems. Since local selection has already been utilized in cellular algorithms in the literature, the main issue of this paper is how to implement the concept of local competition. We show three ideas about its utilization: Local elitism, local ranking, and local replacement. Local elitism and local ranking are used for single-objective optimization to increase the diversity of solutions. On the other hand, local replacement is used for multi-objective optimization to improve the convergence of solutions to the Pareto frontier. The main characteristic feature of our approach is that the two neighborhood structures can be specified independently of each other. Thus, we can separately examine the effect of each neighborhood structure on the behavior of cellular algorithms.

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Acknowledgments

This work was partially supported by Japan Society for the Promotion of Science (JSPS) through Grand-in-Aid for Scientific Research (B): KAKENHI (20300084). Some computational experiments were performed by Mr. Ken Ohara.

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Authors and Affiliations

  1. Graduate School of Engineering, Osaka Prefecture University, Osaka, Japan

    Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto & Yusuke Nojima

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  1. Hisao Ishibuchi
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  2. Yuji Sakane
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  3. Noritaka Tsukamoto
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  4. Yusuke Nojima
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Correspondence to Hisao Ishibuchi.

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Ishibuchi, H., Sakane, Y., Tsukamoto, N. et al. Implementation of cellular genetic algorithms with two neighborhood structures for single-objective and multi-objective optimization. Soft Comput 15, 1749–1767 (2011). https://doi.org/10.1007/s00500-010-0617-8

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