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Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem

Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem

Tabitha James, Cesar Rego
Copyright: © 2011 |Volume: 2 |Issue: 2 |Pages: 19
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781613509326|DOI: 10.4018/jsir.2011040104
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MLA

James, Tabitha, and Cesar Rego. "Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem ." IJSIR vol.2, no.2 2011: pp.52-70. http://doi.org/10.4018/jsir.2011040104

APA

James, T. & Rego, C. (2011). Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem . International Journal of Swarm Intelligence Research (IJSIR), 2(2), 52-70. http://doi.org/10.4018/jsir.2011040104

Chicago

James, Tabitha, and Cesar Rego. "Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem ," International Journal of Swarm Intelligence Research (IJSIR) 2, no.2: 52-70. http://doi.org/10.4018/jsir.2011040104

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Abstract

This paper introduces a new path relinking algorithm for the well-known quadratic assignment problem (QAP) in combinatorial optimization. The QAP has attracted considerable attention in research because of its complexity and its applicability to many domains. The algorithm presented in this study employs path relinking as a solution combination method incorporating a multistart tabu search algorithm as an improvement method. The resulting algorithm has interesting similarities and contrasts with particle swarm optimization methods. Computational testing indicates that this algorithm produces results that rival the best QAP algorithms. The authors additionally conduct an analysis disclosing how different strategies prove more or less effective depending on the landscapes of the problems to which they are applied. This analysis lays a foundation for developing more effective future QAP algorithms, both for methods based on path relinking and tabu search, and for hybrids of such methods with related processes found in particle swarm optimization.

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