Numerical comparison of some penalty-based constraint handling techniques in genetic algorithms

被引：80

作者：

Miettinen, K ^{[1
]}

Mäkelä, MM ^{[1
]}

Toivanen, J ^{[1
]}

机构：

[1] Univ Jyvaskyla, Dept Math Informat Technol, FIN-40014 Jyvaskyla, Finland

来源：

JOURNAL OF GLOBAL OPTIMIZATION | 2003年 / 27卷 / 04期

基金：

芬兰科学院;

关键词：

constrained optimization; genetic algorithms; global optimization; penalty functions;

D O I：

10.1023/A:1026065325419

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We study five penalty function-based constraint handling techniques to be used with genetic algorithms in global optimization. Three of them, the method of superiority of feasible points, the method of parameter free penalties and the method of adaptive penalties have already been considered in the literature. In addition, we introduce two new modifications of these methods. We compare all the five methods numerically in 33 test problems and report and analyze the results obtained in terms of accuracy, efficiency and reliability. The method of adaptive penalties turned out to be most efficient while the method of parameter free penalties was the most reliable.

引用

页码：427 / 446

页数：20

共 33 条

[1] AUGMENTED LAGRANGIAN GENETIC ALGORITHM FOR STRUCTURAL OPTIMIZATION [J].

ADELI, H ;

CHENG, NT .

JOURNAL OF AEROSPACE ENGINEERING, 1994, 7 (01) :104-118

[2]

[Anonymous], 1989, GENETIC ALGORITHM SE

[3]

[Anonymous], 1999, Evolutionary algorithms in engineering and computer science

[4]

[Anonymous], 1995, Handbook of global optimization, Nonconvex Optimization and its Applications

[5]

Bazaraa M.S., 2013, Nonlinear Programming-Theory and Algorithms, V3rd

[6]

Ben Hamida S., 2000, Parallel Problem Solving from Nature PPSN VI. 6th International Conference. Proceedings (Lecture Notes in Computer Science Vol.1917), P529

[7]

Camponogara E, 1997, PROCEEDINGS OF THE THIRD NORDIC WORKSHOP ON GENETIC ALGORITHMS AND THEIR APPLICATIONS (3NWGA), P49

[8] Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art [J].

Coello, CAC .

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2002, 191 (11-12) :1245-1287

[9] Penalty guided genetic search for reliability design optimization [J].

Coit, DW ;

Smith, AE .

COMPUTERS & INDUSTRIAL ENGINEERING, 1996, 30 (04) :895-904

[10] An efficient constraint handling method for genetic algorithms [J].

Deb, K .

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2000, 186 (2-4) :311-338

← 1 2 3 4 →