Constrained optimization problem solving using estimation of distribution algorithms

被引：6
|
作者：
Simionescu, PA [1 ]
Beale, DG [1 ]
Dozier, GV [1 ]
机构：
[1] Auburn Univ, Dept Mech Engn, Auburn, AL 36849 USA
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.2004.1330870
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Two variants of Estimation of Distribution Algorithm (EDA) are tested against solving several continuous optimization problems with constraints. Numerical experiments are conducted and comparison is made between constraint handling using several types of penalty and repair operators in case of both elitist and non-elitist implementations of the EDA's. Graphical display and animations of representative runs of the best and worst performers proved useful in enhancing the understanding of how such algorithms work.
引用
收藏
页码：296 / 302
页数：7
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