Annals of Operations Research

, Volume 247, Issue 2, pp 833–851 | Cite as

Experimental analysis of crossover and mutation operators on the quadratic assignment problem

Article

Abstract

In genetic algorithms crossover is the most important operator where pair of chromosomes and crossover site along their common length are selected randomly. Then the information after the crossover site of the parent chromosomes is swapped. On the other hand, mutation operator randomly alters some genes of a chromosome, and thus diversifies the search space. We consider three crossover and ten mutation operators for the genetic algorithms which are then compared for the quadratic assignment problem on some benchmark QAPLIB instances. The experimental study shows the effectiveness of the sequential constructive crossover and the adaptive mutation operators for the problem.

Keywords

Quadratic assignment problem NP-hard Genetic algorithm  Sequential constructive crossover Adaptive mutation 

Notes

Acknowledgments

The author is very much thankful to the honorable reviewers for their comments and constructive suggestions which helped the author to improve the paper. This research was supported by the NSTIP strategic technologies program number (10) in the Kingdom of Saudi Arabia vide Award No.11-INF1788-08.The author is very much thankful to the NSTIP for its financial and technical supports.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Computer Science, College of Computer and Information SciencesAl Imam Mohammad Ibn Saud Islamic University (IMSIU)RiyadhKingdom of Saudi Arabia

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