文献类型：期刊文献

英文题名：Genetic mechanism-enhanced standard particle swarm optimization 2011

作者：Du, Wenli[1];Zhang, Fei[1]

机构：[1]East China Univ Sci & Technol, Shanghai 200237, Peoples R China

年份：2018

卷号：22

期号：21

起止页码：7207

外文期刊名：SOFT COMPUTING

收录：;EI(收录号：20172903965037);WOS:【SCI-EXPANDED(收录号:WOS:000446414900018)】；

基金：This work was supported by National Natural Science Foundation of China (61590923, 61422303) and "Shu Guang" project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation.

语种：英文

外文关键词：Standard particle swarm optimization 2011; Genetic mechanism; Event-triggered mechanism; Cognitive component; Exploration ability

摘要：Standard particle swarm optimization 2011 (SPSO2011) is a major improvement of the original particle swarm optimization (PSO) with its adaptive random topology and rotational invariance. Its overall performance has also been improved considerably from the original PSO algorithm, but further improvement is still possible. This study attempts to enhance the exploration ability of SPSO2011 further. The enhancement method conditionally introduces a new genetic mechanism to improve the personal best condition of each particle. This conditional event is called an event-triggered mechanism. Moreover, the new genetic mechanism is utilized to crossover, mutate, and select an improved offspring to improve the condition of the cognitive component and indirectly enhance the exploration ability. The proposed algorithm is called genetic mechanism-enhanced SPSO2011 (SPSO2011_GM). SPSO2011_GM is empirically analyzed with 42 benchmark functions. Results confirm the efficiency of the proposed enhancement method and verify the convergence, exploration, reliability, and scalability of the method.