Abstract
Previously, a meta-heuristic approach called Co-Operation of Biology Related Algorithms or COBRA for solving real-parameter optimization problems was introduced and described. COBRA’s basic idea consists in a cooperative work of well-known bio-inspired algorithms, which were chosen due to the similarity of their schemes. COBRA’s performance was evaluated on a set of test functions and its workability was demonstrated. Thus it was established that the idea of the algorithms’ cooperative work is useful. However, it is unclear which bionic algorithms should be included in this cooperation and how many of them. Therefore, the aim of this study was to design a fuzzy logic controller for determining which bio-inspired algorithms should be included in the co-operative work for solving optimization problems using the COBRA approach. The population sizes of the bio-inspired component-algorithms were automatically changed by the obtained controller. The experimental results obtained by the two types of fuzzy-controlled COBRA are presented and their usefulness is demonstrated.
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Acknowledgments
Research is performed with the support of the Ministry of Education and Science of Russian Federation within State Assignment project № 2.1680.2017/ПЧ.
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Akhmedova, S., Semenkin, E., Stanovov, V., Vishnevskaya, S. (2017). Fuzzy Logic Controller Design for Tuning the Cooperation of Biology-Inspired Algorithms. In: Tan, Y., Takagi, H., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2017. Lecture Notes in Computer Science(), vol 10386. Springer, Cham. https://doi.org/10.1007/978-3-319-61833-3_28
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DOI: https://doi.org/10.1007/978-3-319-61833-3_28
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