Robustness using Multi-Objective Evolutionary Algorithms

被引：0
|
作者：
Gaspar-Cunha, A. [1 ]
Covas, J. A. [1 ]
机构：
[1] Univ Minho, IPC, P-4719 Braga, Portugal
来源：
APPLICATIONS OF SOFT COMPUTING: RECENT TRENDS | 2006年
关键词：
multi-objective evolutionary algorithms; robustness;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this work a method to take into account the robustness of the solutions during multi-objective optimization using a Multi-Objective Evolutionary Algorithm (MOEA) was presented. The proposed methodology was applied to several benchmark single and multi-objective optimization problems. A combination of robustness measures and the use of the Reduced Pareto Set Genetic Algorithm with Elitism (RPSGAe), that is an algorithm that distributes the solutions uniformly along the Pareto frontier, provided good results and are expected to be adequate for "real" optimization problems.
引用
收藏
页码：353 / +
页数：3
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