Abstract
This paper presents the novel cooperative metaheuristic algorithm including the flower pollination algorithm (FPA) and the adaptive tabu search named the cooperative FPA-ATS. The proposed cooperative FPA-ATS possesses two states. Firstly, it starts the search for the feasible solutions over entire search space by using the FPA’s explorative property. Secondly, it searches for the global solution by using the ATS’s exploitative property. The cooperative FPA-ATS are tested against ten multimodal benchmark functions for global minimum finding in order to perform its search performance. By comparison with the FPA and ATS, it was found that the cooperative FPA-ATS is more efficient than the FPA and ATS, significantly.
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Niyomsat, T., Hlangnamthip, S., Puangdownreong, D. (2021). Cooperative FPA-ATS Algorithm for Global Optimization. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing and Optimization. ICO 2020. Advances in Intelligent Systems and Computing, vol 1324. Springer, Cham. https://doi.org/10.1007/978-3-030-68154-8_16
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DOI: https://doi.org/10.1007/978-3-030-68154-8_16
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