A Feasibility-Preserving Crossover and Mutation Operator for Constrained Combinatorial Problems

Glaß M, Lukasiewycz M, Teich J (2008)


Publication Type: Conference contribution

Publication year: 2008

Journal

Publisher: Springer-verlag

Edited Volumes: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Series: Lecture Notes in Computer Science (LNCS)

City/Town: Berlin, Heidelberg

Book Volume: 5199

Pages Range: 919-928

Conference Proceedings Title: Proceedings of the 10th International Conference on Parallel Problem Solving from Nature

Event location: Dortmund DE

Journal Issue: 2008

ISBN: 978-3-540-87699-1

URI: http://ls11-www.cs.uni-dortmund.de/ppsn/ppsn10/

DOI: 10.1007/978-3-540-87700-4

Abstract

This paper presents a feasibility-preserving crossover and mutation operator for evolutionary algorithms for constrained combinatorial problems. This novel operator is driven by an adapted Pseudo-Boolean solver that guarantees feasible offspring solutions. Hence, this allows the evolutionary algorithm to focus on the optimization of the objectives instead of searching for feasible solutions. Based on a proposed scalable testsuite, six specific testcases are introduced that allow a sound comparison of the feasibility-preserving operator to known methods. The experimental results show that the introduced approach is superior to common methods and competitive to a recent state-of-the-art decoding technique. © 2008 Springer-Verlag Berlin Heidelberg.

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How to cite

APA:

Glaß, M., Lukasiewycz, M., & Teich, J. (2008). A Feasibility-Preserving Crossover and Mutation Operator for Constrained Combinatorial Problems. In Proceedings of the 10th International Conference on Parallel Problem Solving from Nature (pp. 919-928). Dortmund, DE: Berlin, Heidelberg: Springer-verlag.

MLA:

Glaß, Michael, Martin Lukasiewycz, and Jürgen Teich. "A Feasibility-Preserving Crossover and Mutation Operator for Constrained Combinatorial Problems." Proceedings of the 10th International Conference on Parallel Problem Solving from Nature (PPSN08), Dortmund Berlin, Heidelberg: Springer-verlag, 2008. 919-928.

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