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多目标优化算法

于 2017-05-15 发布 文件大小:2KB
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  目前的多目标优化算法有很多,Kalyanmoy Deb 的 NSGA-II(Nondominated Sorting Genetic Algorithm II,带精英策略的快速非支配排序遗传算法)无疑是其中应用最为广泛也是最为成功的一种。MATLAB 自带的 gamultiobj 函数所采用的算法,就是基于 NSGA-II 改进的一种多目标优化算法(a variant of NSGA-II)。gamultiobj 函数的出现,为在 MATLAB 平台下解决多目标优化问题提供了良好的途径。gamultiobj 函数包含在遗传算法与直接搜索工具箱(Genetic Algorithm and Direct Search Toolbox, GADST)中,这里我们称 gamultiobj 函数为基于遗传算法的多目标优化函数,相应的算法为基于遗传算法的多目标优化算法。本案例将以 gamultiobj 函数为基础,对基于遗传算法的多目标优化算法进行讲解,并详细分析其代码,同时通过一个简单的案例介绍 gamultiobj 函数的使用。 ( (U09) u5126 u591A u591A u5108 u7R2 U7565 u7654 u5EB2 u09A1 u653H U4E5F u662F u6700 u4E3A u6210 u529F u7684 u4E00 u79CD u3002MATLAB u81EA u5E26 u7684 gamultiobj u51FD u6570 u6240 u91C7 u7528 u7689 u7B97 u6CD5 uFF0C u5C31 u662F U57FA u4E8E NSGA-II u6539 u8FDB u7684 u4E00 u79CD u591A u76EE u6807 u4161 u5316 u7B97 u6CD5 uFF08a variant of NSGA-II uFF09 u3002gamultiobj u51FD u6570 u7684 u5150 U73B0 uFF0C u4E3A u5728 MATLAB u5E73 u53F0 u8E0B u89E3 u51B3 u5B1 u591A u76EE u6807 u4F18 u5316 u95EE u9898 u63D0 u4F9B u4E86 u826F u597D u7944 u9014 u5F84 u3002gamultiobj U5135 u5135 u5255 u5135 u5255 u5135 u7R2 u7R2 u7B97 F0C u8FD9 u91CC u6211 u4EEC u79F0 gamultiobj u51FD u6570 u4E3A u57FA u4E8E u907 u4F20 u7B97 u6CD5 u7684 u591A u76EE u6807 u4F18 u5316 u51FD u6570 uFF0C u76F8 U5E94 u7689 u7B97 u6CD2 u4E3A u57FA u4E8E u9057 u4F20 u7B97 u6CD5 u7684 u591A u76EE u6807 )

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基于遗传算法的多目标优化算法.txt,2624,2017-05-15

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