An empirical study about the usefulness of evolution strategies to solve constrained optimization problems

被引:427
作者
Mezura-Montes, Efren [1 ]
Coello Coello, Carlos A. [2 ]
机构
[1] Natl Lab Adv Informat LANIA AC, Ctr Xalapa 91000, Veracruz, Mexico
[2] CINVESTAV IPN, Dept Comp Sci, Evolutionary Computat Grp EVOCINV, Mexico City 07300, DF, Mexico
关键词
global optimization; evolutionary algorithms; constraint handling; engineering design;
D O I
10.1080/03081070701303470
中图分类号
TP301 [理论、方法];
学科分类号
081202 [计算机软件与理论];
摘要
In this paper, we explore the capabilities of different types of evolution strategies (ES) to solve global optimization problems with constraints. The aim is to highlight the idea that the selection of the search engine is more critical than the selection of the constraint-handling mechanism, which can be very simple indeed. We show how using just three simple comparison criteria based on feasibility, the simple evolution strategy can be led to the feasible region of the search space and find the global optimum solution (or a very good approximation of it). Different ES including a variation of a (mu + 1) - ES and (mu,(+) lambda) with or without correlated mutation were implemented. Such approaches were tested using a well-known test suite for constrained optimization. Furthermore, the most competitive version found (among those five) was compared against three state-of-the-art approaches and it was also compared against a GA using the same constraint-handling approach. Finally, our evolution strategy was used to solve some engineering design problems.
引用
收藏
页码:443 / 473
页数:31
相关论文
共 48 条
[1]
A socio-behavioural simulation model for engineering design optimization [J].
Akhtar, S ;
Tai, K ;
Ray, T .
ENGINEERING OPTIMIZATION, 2002, 34 (04) :341-354
[2]
[Anonymous], 1103468 AEG FORSCH
[3]
[Anonymous], T ASME J MECH DES, DOI DOI 10.1115/1.2919393
[4]
Arnold D. V., 2002, Genetic Algorithms and Evolutionary Computation
[5]
Arora J., 2004, Introduction to Optimum Design
[6]
Back T., 1991, P 4 INT C GEN ALG, P2
[7]
Back T., 1996, Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms
[8]
Belegundu A.D., 1982, STUDY MATH PROGRAMMI
[9]
Beyer H.-G., 2001, NAT COMP SER
[10]
Coello C.A., 2002, Evolutionary Algorithms for Solving Multi-Objective Problems