| Citation: | GUO Qing, HUI Xiaobin, ZHANG Jiakui, et al. Improved flower pollination algorithm for multimodal function optimization[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(4): 828-840. doi: 10.13700/j.bh.1001-5965.2017.0240(in Chinese)
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In order to discuss the defects of flower pollination algorithm (FPA) in solving multimodal optimization problems, the optimal disadvantages of flower pollination algorithm in multimodal function optimization were qualitatively analyzed by defining population diversity and difference index. And then a new framework of FPA was constructed by optimizing the global pollination process based on the simulated annealing idea and using Nelder-Mead simplex search method to reconstruct the local pollination process. The simulation results show that the improved flower pollination algorithm can effectively avoid falling into local optimum and has better global exploration and local exploitation abilities, which has advantages to solve multimodal function optimization, compared with primary flower pollination algorithm, cuckoo search algorithm and firefly algorithm.
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