Constraint handling in genetic algorithms using a gradient-based repair method

Constraint handling in genetic algorithms using a gradient-based repair method

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Article ID: iaor20072025
Country: United Kingdom
Volume: 33
Issue: 8
Start Page Number: 2263
End Page Number: 2281
Publication Date: Aug 2006
Journal: Computers and Operations Research
Authors: ,
Keywords: programming: constraints
Abstract:

Constraint handling is one of the major concerns when applying genetic algorithms (GAs) to solve constrained optimization problems. This paper proposes to use the gradient information derived from the constraint set to systematically repair infeasible solutions. The proposed repair procedure is embedded into a simple GA as a special operator. Experiments using 11 benchmark problems are presented and compared with the best known solutions reported in the literature. Our results are competitive, if not better, compared to the results reported using the homomorphous mapping method, the stochastic ranking method, and the self-adaptive fitness formulation method.

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