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Numerical Comparison of Some Penalty-Based Constraint Handling Techniques in Genetic Algorithms

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Abstract

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.

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Authors and Affiliations

  1. Department of Mathematical Information Technology, University of Jyväskylä, Finland, P.O. Box 35 (Agora), FIN-40014

    Kaisa Miettinen, Marko M. Mäkelä & Jari Toivanen

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  1. Kaisa Miettinen
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  2. Marko M. Mäkelä
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  3. Jari Toivanen
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Miettinen, K., Mäkelä, M.M. & Toivanen, J. Numerical Comparison of Some Penalty-Based Constraint Handling Techniques in Genetic Algorithms. Journal of Global Optimization 27, 427–446 (2003). https://doi.org/10.1023/A:1026065325419

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