计算机应用研究2017，Vol.34Issue(8)：2364-2367,4.DOI:10.3969/j.issn.1001-3695.2017.08.029
基于等高替换和随机反向的粒子群算法
Particle swarm optimization algorithm based onequal replacement and random opposition
摘要
Abstract
In order to overcome the shortcomings of conventional particle swarm optimization (PSO) algorithm, such as easily trapping in local optima and lower search accuracy, this paper proposed a different random replacement strategy based on contour.On the basis of the strategy, the algorithm used the simplified particle swarm to update particles, and it speeded up the searching capability of the particled.In order to ensure the global search ability of the algorithm, it put forward the optimal random search strategy in the opposite direction for some particles with worst adaptive value.The algorithm tested on seven distinct types of benchmark functions.The results show that the proposed algorithm can maintain the diversity of particles with strong global search capability, with higher convergence rate and accuracy.关键词
简化粒子群/等高替换/最优随机反向Key words
simple particle swarm/equal replacement/random opposition of optimal分类
信息技术与安全科学引用本文复制引用
陈群林,高岳林,郭祥..基于等高替换和随机反向的粒子群算法[J].计算机应用研究,2017,34(8):2364-2367,4.基金项目
国家自然科学基金资助项目(6156001) （6156001）
北方民族大学重点科研资助项目(2015KJ10) （2015KJ10）
陕西省自然科学基础研究计划资助项目(2014JM2-6098) （2014JM2-6098）
