Journal of Industrial Engineering International
, 8:6
First online:
Effective heuristics and metaheuristics for the quadratic assignment problem with tuned parameters and analytical comparisons
 Mahdi BashiriAffiliated withDepartment of Industrial Engineering, Shahed University Email author
 , Hossein KarimiAffiliated withDepartment of Industrial Engineering, Shahed University
Abstract
Quadratic assignment problem (QAP) is a wellknown problem in the facility location and layout. It belongs to the NPcomplete class. There are many heuristic and metaheuristic methods, which are presented for QAP in the literature. In this paper, we applied 2opt, greedy 2opt, 3opt, greedy 3opt, and VNZ as heuristic methods and tabu search (TS), simulated annealing, and particle swarm optimization as metaheuristic methods for the QAP. This research is dedicated to compare the relative percentage deviation of these solution qualities from the best known solution which is introduced in QAPLIB. Furthermore, a tuning method is applied for metaheuristic parameters. Results indicate that TS is the best in 31%of QAPs, and the IFLS method, which is in the literature, is the best in 58 % of QAPs; these two methods are the same in 11 % of test problems. Also, TS has a better computational time among heuristic and metaheuristic methods.
Keywords
Quadratic assignment problem Heuristics Metaheuristics Tuning method Title
 Effective heuristics and metaheuristics for the quadratic assignment problem with tuned parameters and analytical comparisons
 Open Access
 Available under Open Access This content is freely available online to anyone, anywhere at any time.
 Journal

Journal of Industrial Engineering International
8:6
 Online Date
 July 2012
 DOI
 10.1186/2251712X86
 Print ISSN
 17355702
 Online ISSN
 2251712X
 Publisher
 Springer Berlin Heidelberg
 Additional Links
 Topics
 Keywords

 Quadratic assignment problem
 Heuristics
 Metaheuristics
 Tuning method
 Authors

 Mahdi Bashiri ^{(1)}
 Hossein Karimi ^{(1)}
 Author Affiliations

 1. Department of Industrial Engineering, Shahed University, Tehran, 3319118651, Iran