四川大学学报（自然科学版）2017，Vol.54Issue(4)：721-727,7.DOI:10.3969/j.issn.0490-6756.2017.04.010
基于动态多子族群自适应群居蜘蛛优化算法
An adaptation social spider optimization algorithm based on dynamic multi-swarm strategy
摘要
Abstract
In order to improve the samples diversity and convergence properties of social spiders optimization algorithm (SSO),an adaptation social spider optimization algorithm based on dynamic multi-swarm strategy (DMASSO) is proposed.According to the algorithm samples diversity and evolutionary level,the spider population is dynamically divided into different sizes leading groups and supporting groups,and the adaptive learning factor and Gaussian disturbance factor are introduced to improve the algorithm update ways,which helps to improve the algorithm global optimization ability and maintain the diversity of the sample population.For the test results of typical characteristics functions show that compared to SSO algorithm,SFLA algorithm and other optimization algorithms,the new algorithm has better convergence speed and convergence accuracy.关键词
群居蜘蛛优化算法/多子族群/自适应/函数优化Key words
Social spider optimization algorithm/Multi-swarm/Adaptation/Function optimization分类
信息技术与安全科学引用本文复制引用
刘洲洲,李彬..基于动态多子族群自适应群居蜘蛛优化算法[J].四川大学学报（自然科学版）,2017,54(4):721-727,7.基金项目
国家自然科学基金(61401499) （61401499）
陕西省教育厅科研计划项目(16JK1395) （16JK1395）
陕西省自然科学研究计划面上项目基金(2017JM6096) （2017JM6096）
