多目标优化的遗传算法及其实现 |
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引用本文: | 胡贵强.多目标优化的遗传算法及其实现[J].渝西学院学报(自然科学版),2008(5):12-15. |
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作者姓名: | 胡贵强 |
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作者单位: | 西南大学计算机与信息科学学院 |
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摘 要: | 遗传算法是一种通过模拟自然进化过程搜索最优解的方法,在优化方法中具有独特的优越性,有着非常重要的理论意义和广泛的应用领域.多目标优化问题求解已成为遗传算法的一个重要研究方向,而基于Pareto最优概念的多目标遗传算法则是当前遗传算法的研究热点.本文对遗传算法的理论基础进行分析,包括模式定理等,讨论用遗传算法来解决多目标优化问题的方法并给出其实现,介绍遗传算法的各种改进措施,并指出遗传算法的发展动向.
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关 键 词: | 遗传算法 多目标优化 Pareto最优 |
The Research and Implementation of Genetic Algorithm for Multi-Objective Optimization |
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Authors: | HU Gui-qiang |
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Institution: | HU Gui - qiang (Computer Department, Southwest China University, Chongqing 400715 , China) |
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Abstract: | Genetic Algorithms(GAs) are stochastical search and optimization techniques which mimic the natural process of evolution.GAs have some advantages over the traditional optimization algorithms,and are of the great importance and have a wide range of applications.Multi-Objective Optimization(MOO) has been an important research area of Genetic Algorithms in recent years,and current research work focuses on the Pareto optimal-based MOO evolutionary approaches.The basic algorithm theory and implementation techniques of genetic algorithms are outlined.The implementation of Multi-Objective optimization problem has been given.This paper has also summed up some kinds of relevant improved methods and some new developmental trends concerning genetic algorithms. |
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Keywords: | Genetic Algorithms Multi-Objective Optimization Pareto optimal |
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