Abstract
In order to improve the particle swarm optimizer (PSO) for solving complex multimodal problems, an improved PSO with full information and mutation operator (PSOFIM) is proposed base basic PSO and mutation thought. In PSOFIM, a novel mutation is adopted to improve the history optimal position of particle (pbest) by disturbance in operation of each dimension. Additionally, a full information strategy for each particle is introduced to make best use of each dimension of each particle to ensure the information utility for swarm topology where each particle learns from its neighborhood information for his optimal position to improve itself study ability, whose strategies improve the swarm fly to the probability of the optimal solution. The simulation experiment results of benchmark function tests show PSOFIM has better performance than the basic PSO algorithm.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (Grants nos. 71461027, 71471158). Science and technology talent training object of Guizhou province outstanding youth (Qian ke he ren zi [2015] 06); Guizhou province natural science foundation in China (Qian Jiao He KY [2014] 295); 2013, 2014 and 2015 Zunyi 15851 talents elite project funding; Zunyi innovative talent team (Zunyi KH (2015) 38); Project of teaching quality and teaching reform of higher education in Guizhou Province (Qian Jiao gaofa [2013] 446, [2015] 337), College students’ innovative entrepreneurial training plan (201410664004, 201510664016); Guizhou science and technology cooperation plan (Qian Ke He LH zi [2015] 7050, Qian Ke He J zi LKZS [2014] 30, Qian Ke He LH zi [2016] 7028); Zunyi Normal College Research Funded Project (2012 BSJJ19).
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Liu, Y., Li, C., Wu, X., Zeng, Q., Liu, R., Huang, T. (2016). Particle Swarm Optimizer with Full Information. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_64
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DOI: https://doi.org/10.1007/978-3-319-42291-6_64
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