电子学报Issue(8)：1538-1544,7.DOI:10.3969/j.issn.0372-2112.2015.08.011
一种多策略融合的多目标粒子群优化算法
A MuIti-Objective ParticIe Swarm Optimization AIgorithm Integrating MuItipIy Strategies
摘要
Abstract
In order to improve the overall performance of multi-objective particle swarm optimization algorithm (MOPSO) in solving complicated multi-objective optimization problems,a multi-objective particle swarm optimization algorithm integrating multiply strategies (MSMOPSO)was proposed in the paper.A new initialization approach of combining uniformization and random-ization was adopted in the MSMOPSO.Secondly,a disturbance item was added to the particle’s velocity updating formula.Thirdly, a simplified k-nearest neighbor approach was applied to preserve the diversity of external archive.Finally,every non-dominated par-ticle in the external archive was assigned the property of lifespan and the lifespan value would be adjusted dynamically during the run of the MSMOPSO.The experimental results illustrate that the proposed algorithm significantly outperforms the other five peer competitors in terms of GD,SP on ZDT and DTLZ test instances set.关键词
粒子群优化/多策略融合/多目标优化问题/多目标粒子群优化算法Key words
particle swarm optimization/integrating multiply strategies/multi-objective optimization problem/multi-objective particle swarm optimization algorithm分类
信息技术与安全科学引用本文复制引用
谢承旺,邹秀芬,夏学文,王志杰..一种多策略融合的多目标粒子群优化算法[J].电子学报,2015,(8):1538-1544,7.基金项目
国家自然科学基金（No．61165004）；国家自然科学基金重大研究计划培育项目（No．91230118）；江西省自然科学基金（No．20114BAB201025）；江西省教育厅科技项目 （）
