A method of genetic algorithm based multiobjective optimization via cooperative coevolution

被引：0
|
作者：
Jongsoo Lee
Doyoung Kim
机构：
[1] Yonsei University,School of Mechanical Engineering
来源：
Journal of Mechanical Science and Technology | 2006年 / 20卷
关键词：
Multi objective Optimization; Pareto Optimal; Genetic Algorithm; Coevolution; Penalty on Difference;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.
引用
收藏
页码：2115 / 2123
页数：8
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