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

Penalty Function Methods for Constrained Optimization with Genetic Algorithms

Hacettepe University, Faculty of Science Department of Statistics, 06532, Beytepe, Ankara
Published: 1 April 2005
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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 Genetic algorithms; Optimization, Constraint handling; Penalty function
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Yeniay, Ö. Penalty Function Methods for Constrained Optimization with Genetic Algorithms. Math. Comput. Appl. 2005, 10, 45-56.

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Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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