计算机工程与应用2011，Vol.47Issue(12)：23-26,4.DOI:10.3778/j.issn.1002-8331.2011.12.007
解决约束优化问题的改进粒子群算法
Improved particle swarm optimizer for constrained optimization problems.
摘要
Abstract
An improved particle swarm optimizer is proposed for solving constrained optimization problems(CMPSO).In order to increase the diversity of the swarm and improve the ability to escape from local optima,the diversity threshold value (λa) is introduced. Whan the swarm diversity value is equal or lesser than λa, the polynomial mutation is invoked for the global best performing particle(Gbest) and the particle personal best performing particle(Pbest).A new comparison strategy is proposed based on the violation degree of each particle, which can keep some infeasible solutions that have the good performance. To improve probability of flying to the optimal solution,a comprehensive learning strategy is adopted. The experiments on benchmarks indicate that the proposed algorithm is a feasible algorithm for solving constrained optimization problems关键词
粒子群算法/约束优化/种群多样性Key words
Particle Swarm Optimizer(PSO)/constrained optimization/swarm diversity分类
信息技术与安全科学引用本文复制引用
刘衍民,隋常玲,牛奔..解决约束优化问题的改进粒子群算法[J].计算机工程与应用,2011,47(12):23-26,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.71001072) （the National Natural Science Foundation of China under Grant No.71001072）
贵州教育厅社科项目(No.0705204) （No.0705204）
遵市科技局项目(No.[2008]21). （No.[2008]21）
