计算机工程与应用Issue(9)：50-53,4.DOI:10.3778/j.issn.1002-8331.1112-0500
自适应约束优化混合粒子群算法
Adaptive constrained optimization hybrid Particle Swarm Optimization algorithm
龚国斌1
作者信息
- 1. 宜春学院 数学与计算机学院，江西 宜春 336000
- 折叠
摘要
Abstract
A hybrid Particle Swarm Optimization algorithm is proposed for solving constrained optimization problems. The primary features of the algorithm proposed are as follows. As for search mechanism, chaotic initialization is introduced to improve the quality of initial population. The Cauchy mutation operator is introduced which can expand the search range. The simplex cross-over operator is used to enrich the exploratory and exploitative abilities of the algorithm proposed. As for constraint-handling technique, a new individual comparison criterion is proposed, which can adaptively select different individual comparison crite-ria according to the proportion of feasible solution in current population. The proposed algorithm is tested on several well-known benchmark problems, and the results show that it is effective.关键词
约束优化问题/粒子群优化算法/自适应/混沌Key words
constrained optimization problems/Particle Swarm Optimization(PSO)algorithm/adaptive/chaos分类
信息技术与安全科学引用本文复制引用
龚国斌..自适应约束优化混合粒子群算法[J].计算机工程与应用,2013,(9):50-53,4.
