In this paper, the two hybrid swarm-based metaheuristic algorithms are tested and compared. The first hybrid is already existing Firefly Particle Swarm Optimization (FFPSO), which is based, as the name suggests, on Firefly Algorithm (FA) and Particle Swarm Optimization (PSO). The secondly proposed hybrid is an algorithm using the multi-swarm method to merge FA and PSO. The performance of our developed algorithm is tested and compared with the FFPSO and canonical FA. Comparisons have been conducted on five selected benchmark functions, and the results have been evaluated for statistical significance using Friedman rank test.
CITATION STYLE
Kadavy, T., Pluhacek, M., Viktorin, A., & Senkerik, R. (2018). Multi-swarm optimization algorithm based on firefly and particle swarm optimization techniques. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10841 LNAI, pp. 405–416). Springer Verlag. https://doi.org/10.1007/978-3-319-91253-0_38
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