吉林大学学报（信息科学版）2012，Vol.30Issue(2)：131-137,7.
基于新型Memetic算法的多目标优化
Multi-Objective Optimization Based on Memetic Algorithm
摘要
Abstract
In order to solve multi-objective optimization problems,a newmemetic algorithm is proposed, which combines the global search ability of particle swarm optimization with synchronous local search heuristic for directed local fine-tuning. A new particle updating strategy is presented to deal with the problem of premature convergence and diversity maintenance in the swarm based upon the concept of fuzzy global-best. The proposed new features are verified to show their individual and combined effect in multi-objective optimization. The reactive power optimization result of IEEE14 node system by the new memetic shows that it has a good astringency and efficiency.关键词
memetic算法/多目标优化/粒子群算法Key words
memetic algorithm/multi-objective optimization/particle swarm optimization分类
信息技术与安全科学引用本文复制引用
刘伟,赵丹,孙宏伟..基于新型Memetic算法的多目标优化[J].吉林大学学报（信息科学版）,2012,30(2):131-137,7.基金项目
黑龙江省普通高等学校青年学术骨干基金资助项目(1055G04) （1055G04）
