Multi-objective optimization scheme using Pareto Genetic Algorithm

被引：0
|
作者：
Qin, YT [1 ]
Ma, LH [1 ]
机构：
[1] Zhejiang Univ, Inst Syst Engn, Hangzhou 310027, Peoples R China
来源：
ICCC2004: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION VOL 1AND 2 | 2004年
关键词：
multi-objective optimization; self-adaptive; Pareto Genetic Algorithm;
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：
Stochastic and implicitly parallel properties of Genetic Algorithm (GA) make it possible to search for multiple local optimal solutions and obtain optimal solution set. Based on self-adaptive genetic algorithm, a Pareto Genetic Algorithm (PGA) which introduces population-ranking technique, niche technique and elitism is developed in this paper. The search process of the PGA is speeded up and the distribution of the solution on the Pareto front is improved. From Pareto front designers may select some suitable solution according to their inclination.
引用
收藏
页码：1754 / 1757
页数：4
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