引用本文:刘淳安,王宇平.基于一种新模型的多目标遗传算法及性能分析[J].控制理论与应用,2006,23(3):425~428.[点击复制]
LIU Chun-an,WANG Yu-ping.Multi-objective genetic algorithm based on a new model and analysis of its performance[J].Control Theory and Technology,2006,23(3):425~428.[点击复制]
基于一种新模型的多目标遗传算法及性能分析
Multi-objective genetic algorithm based on a new model and analysis of its performance
摘要点击 1354  全文点击 960  投稿时间:2004-12-31  修订日期:2005-08-16
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DOI编号  10.7641/j.issn.1000-8152.2006.3.018
  2006,23(3):425-428
中文关键词  多目标优化  遗传算法  Pareto最优解  U-度量
英文关键词  multi-objective optimization  genetic algorithm  Pareto optimal solution  U-measure
基金项目  国家自然科学基金资助项目(60374063); 陕西省自然科学研究计划项目(2001SL06); 宝鸡文理学院院重点级科研计划项目(ZK2548)
作者单位
刘淳安,王宇平 西安电子科技大学理学院,陕西西安710071
宝鸡文理学院数学系,陕西宝鸡721007
西安电子科技大学计算机学院,陕西西安710071 
中文摘要
      在多目标优化中,各目标通常相互冲突,其最优解往往有无穷多个,如何在最优解集中求出一组分布均匀且数量多的Pareto最优解供决策者选择十分重要.本文给出了多目标优化的一种新解法.首先定义了种群序值的理想方差和种群密度的方差,然后把目标个数任意的多目标函数优化问题Ⅰ转化成了用种群序值的理想方差和种群密度的方差构成的两个目标函数的优化问题Ⅱ,并对转化后的优化问题Ⅱ提出了一种新的多目标遗传算法(RDMOEA).计算机仿真表明RDMOEA算法对不同的实验函数均可求出在最优解集合中分布均匀且数量充足的Pareto最优
英文摘要
      Multi-objective optimization problems often involve incommensurable and competing objectives,and the number of their Pareto optimal solutions is usually infinite,thus it is very important to find a sufficient number of uniformly distributed Pareto optimal solutions for the decision maker.A novel algorithm is presented to solve the multi-objective optimization problem in this paper.The ideal variance of rank of the population and the variance of density of the population are firstly given.Using the ideal variance of rank of the population and the variance of density of the population as two objective functions,the multi-objective optimization problem Ⅰ is then converted into a bi-objective optimization problem Ⅱ.For the transformed problem Ⅱ,a novel multi-objective optimization genetic algorithm(RDMOEA) is also proposed.Finally,computer simulations for the three difficult standard benchmark functions are performed to verify the results.