Penalty Function Methods for Constrained Optimization with Genetic Algorithms

Özgür Yeniay

doi:10.3390/mca10010045

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1 April 2005

Penalty Function Methods for Constrained Optimization with Genetic Algorithms

Hacettepe University, Faculty of Science Department of Statistics, 06532, Beytepe, Ankara

Math. Comput. Appl.2005, 10(1), 45-56;https://doi.org/10.3390/mca10010045

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Abstract

Genetic Algorithms are most directly suited to unconstrained optimization. Application of Genetic Algorithms to constrained optimization problems is often a challenging effort. Several methods have been proposed for handling constraints. The most common method in Genetic Algorithms to handle constraints is to use penalty functions. In this paper, we present these penalty-based methods and discuss their strengths and weaknesses.

Keywords:

Genetic algorithms; Optimization, Constraint handling; Penalty function

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