A COMPARISON OF EVOLUTIONARY PROGRAMMING AND GENETIC ALGORITHMS ON SELECTED CONSTRAINED OPTIMIZATION PROBLEMS

被引：61
|
作者：
FOGEL, DB
机构：
[1] Natural Selection, Inc., La Jolla, CA 92037
来源：
SIMULATION | 1995年 / 64卷 / 06期
关键词：
EVOLUTIONARY PROGRAMMING; GENETIC ALGORITHMS; CONSTRAINED OPTIMIZATION;
D O I：
10.1177/003754979506400605
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Evolutionary programming and genetic algorithms are compared on two constrained optimization problems. The constrained problems are redesigned as related unconstrained problems by the application of penalty functions. The experiments indicate that evolutionary programming outperforms the genetic algorithm. The results are statistically significant under nonparametric hypothesis testing. The results also indicate potential difficulties in the design of suitable penalty functions for constrained optimization problems. A discussion is offered regarding the suitability of different methods of evolutionary computation for such problems.
引用
收藏
页码：397 / 404
页数：8
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