多目标优化问题中一种改进的遗传算法  

An Improved Genetic Algorithm in Multi-Objective Optimization

作　　者：杨金明[1] 吴捷[1] 钟丹虹[1] 

机构地区：[1]华南理工大学电力学院,广东广州510640

出　　处：《华南理工大学学报（自然科学版）》2001年第12期65-67,共3页Journal of South China University of Technology(Natural Science Edition)

摘　　要：遗传算法作为一种随机优化算法在多目标优化等众多领域取得广泛的应用 .针对基本遗传算法存在的寻优速度较慢、存在“封闭竞争”等问题 ,利用生物界中存在的“杂交”优势原理 ,提出以多种群变异为基础解决以上问题的改进遗传算法 。Genetic algorithm, as a random optimization algorithm, has been used in many fields such as multi_objective optimization. In view of the slow computational rate and close competition of simple genetic algorithm, we propose an improved genetic algorithm using the multiple farm variation based on the biological theory of intercross advantage, optimal results have been achieved through simulation.

关 键 词：多目标优化 遗传算法 多种群变异 随机优化 “杂交”优势原理 寻优速度 

分 类 号：O221.6[理学—运筹学与控制论] O242.23[理学—数学]