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

Zakir Hussain Ahmed ()
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Zakir Hussain Ahmed: Al Imam Mohammad Ibn Saud Islamic University (IMSIU)

Annals of Operations Research, 2016, vol. 247, issue 2, No 22, 833-851

Abstract: 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 (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10479-015-1848-y

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