中南民族大学学报：自然科学版2011，Vol.30Issue(3)：89-93,5.
一种多项指标全提升的多目标优化演化算法
A Multi-Objective Optimization Evolutionary Algorithm with Multiple Indicators Enhanced
摘要
Abstract
Currently,most of multi-objective optimization evolutionary algorithms are complex and time-consuming.At the same time,the approximate Pareto fronts of these algorithms may not have enough points,with uneven in distribution and incomplete coverage.This paper presents a new multi-objective optimization evolutionary algorithm,which is based on Particle Swarm Optimization algorithm and Geometric Pareto selection algorithm.The experimental results on five widely used test-problems show that the performance indicators,including the numbers of front points,the uniformity,the complete of coverage and so on,are better than the compared popular multi-objective optimization algorithms： NSGA2,SPEA2,PESA etc.with satisfactory time consuming关键词
演化算法/多目标优化/粒子群优化Key words
evolutionary 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
宋中山,陈建国,郑波尽..一种多项指标全提升的多目标优化演化算法[J].中南民族大学学报：自然科学版,2011,30(3):89-93,5.基金项目
国家自然科学基金资助项目(60803095) （60803095）
