A hierarchical evolutionary approach to multi-objective optimization

被引：2
|
作者：
Mumford, CL [1 ]
机构：
[1] Cardiff Univ, Sch Comp Sci, Cardiff CF24 3XF, S Glam, Wales
来源：
CEC2004: PROCEEDINGS OF THE 2004 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2 | 2004年
关键词：
D O I：
10.1109/CEC.2004.1331134
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes a hierarchical evolutionary approach to Pareto-based multi-objective optimization. Using the SEAMO algorithm (a simple evolutionary algorithm for multi-objective optimization) as a basis, it demonstrates how it is possible to obtain a better spread of results if subpopulations of various sizes are used in a simple hierarchical framework. Three alternative hierarchical models are tried and the results compared.
引用
收藏
页码：1944 / 1951
页数：8
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