Study on multi-objective genetic algorithm

被引：0
|
作者：
Gao, Y [1 ]
Shi, L [1 ]
Yao, PJ [1 ]
机构：
[1] Dalian Univ Technol, Inst Proc Syst Engn, Dalian 116012, Peoples R China
来源：
PROCEEDINGS OF THE 3RD WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-5 | 2000年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Multi-objective genetic algorithm (MOGA) is on affective approach in solving multi-objective optimization problems. The current multi-objective genetic algorithms are reviewed in this paper, and II new form of MOGA, steady-state non-dominated sorting genetic algorithm (SNSGA), is realized by combining the steady-state ideas in single objective genetic algorithm (SOGA) and the fitness assignment strategy of non-dominated sorting genetic algorithm. The fitness assignment strategy fr improved and a new self-adaptive decision scheme of sigma (share) is proposed. This algorithm is proved to be successful with some test problems including GA difficult problem and GA deceptive problem.
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收藏
页码：646 / 650
页数：5
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