On the convergence of multiobjective evolutionary algorithms

被引：121
|
作者：
Hanne, T [1 ]
机构：
[1] Fern Univ Hagen, Dept Econ, D-58084 Hagen, Germany
来源：
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | 1999年 / 117卷 / 03期
关键词：
multi-criteria analysis; stochastic search; evolutionary algorithms; selection mechanism; epsilon-efficient solution; convergence;
D O I：
10.1016/S0377-2217(98)00262-8
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
We consider the usage of evolutionary algorithms for multiobjective programming (MOP), i.e. for decision problems with alternatives taken from a real-valued vector space and evaluated according to a vector-valued objective function. Selection mechanisms, possibilities of temporary fitness deterioration, and problems of unreachable alternatives for such multiobjective evolutionary algorithms (MOEAs) are studied. Theoretical properties of MOEAs such as stochastic convergence with probability 1 are analyzed. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：553 / 564
页数：12
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