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- Title
基于 Levy 变异的反向粒子群优化算法.
- Authors
南杰琼; 王晓东
- Abstract
In order to balance the global search and local search performance of particle swarm algorithm, and overcome the disadvantage of easy to fall into local extremum, a method of opposition-based particle swarm optimization based on Levy variation is proposed. The algorithm adopts the opposition-based learning strategy and an improved search strategy with Levy flight characteristics, and uses the position factor and speed factor to judge the stagnation particles. Then six typical benchmark functions used to compare the search results of the new algorithm with the standard particle swarm algorithm and opposition-based particle swarm algorithm, and the results show that the new algorithm is superior to the other two algorithms in the early search capability and the later search precision.
- Publication
Basic Sciences Journal of Textile Universities / Fangzhi Gaoxiao Jichu Kexue Xuebao, 2018, Vol 31, Issue 1, p115
- ISSN
1006-8341
- Publication type
Article
- DOI
10.13338/j.issn.1006-8341.2018.01.019