NSGA-II:多目标优化遗传算法实现,高效排序与精英策略

This is a python implementation of NSGA-II algorithm. NSGA is a popular non-domination based genetic algorithm for multi-objective optimization. It is a very effective algorithm but has been generally criticized for its computational complexity, lack of elitism and for choosing the optimal parameter value for sharing parameter σshare. A modified version, NSGA II was developed, which has a better sorting algorithm , incorporates elitism and no sharing parameter needs to be chosen a priori.

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项目介绍

这是NSGA-II算法的Python实现。NSGA是一种基于非支配准则的多目标优化遗传算法,广受欢迎。尽管这是一种非常有效的算法,但它因计算复杂性、缺乏精英主义以及在确定共享参数σshare的最优值方面受到了普遍批评。为此,开发了一个改进版本——NSGA II,它具备更优秀的排序算法,融入了精英主义策略,且无需预先选择共享参数。【此简介由AI生成】

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