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An Efficient Method for Maintaining Diversity in Evolutionary Multi-objective Optimization

机译:进化多目标优化中保持多样性的一种有效方法

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Diversity maintenance of solutions is a crucial part in multi-objective optimization. In this paper, a maintenance method which is based on minimum spanning tree is proposed. The proposed method defines a density estimation metric ȁ3; Minimum Spanning Tree Crowding Distance (MSTCD). Moreover, information of degree of solution combined with MSTCD is employed to truncate population. From an extensive comparative study with three other methods on a number of two and three objective test problems, it is observed that the proposed algorithm has good performance in distribution.
机译:解决方案的多样性维护是多目标优化中的关键部分。本文提出了一种基于最小生成树的维护方法。所提出的方法定义了密度估计量度ȁ3;最小生成树拥挤距离(MSTCD)。此外,结合MSTCD的溶解度信息用于截断种群。通过与其他三种方法对两个和三个客观测试问题进行的广泛比较研究,可以看出该算法在分布上具有良好的性能。

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