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

被引：0
|
作者：
Zheng, Jinhua [1 ]
Li, Miqing [1 ]
机构：
[1] Xiangtan Univ, Inst Informat Engn, Xiangtan 411105, Hunan, Peoples R China
来源：
ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 6, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/ICNC.2008.620
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 - 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.
引用
收藏
页码：462 / 467
页数：6
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