DocumentCode
237460
Title
Hybrid metaheuristics for solving the quadratic assignment problem and the generalized quadratic assignment problem
Author
Gunawan, Aldy ; Kien Ming Ng ; Kim Leng Poh ; Hoong Chuin Lau
Author_Institution
Living Analytics Res. Centre, Singapore Manage. Univ., Singapore, Singapore
fYear
2014
fDate
18-22 Aug. 2014
Firstpage
119
Lastpage
124
Abstract
This paper presents a hybrid metaheuristic for solving the Quadratic Assignment Problem (QAP). The proposed algorithm involves using the Greedy Randomized Adaptive Search Procedure (GRASP) to construct an initial solution, and then using a hybrid Simulated Annealing and Tabu Search (SA-TS) algorithm to further improve the solution. Experimental results show that the hybrid metaheuristic is able to obtain good quality solutions for QAPLIB test problems within reasonable computation time. The proposed algorithm is extended to solve the Generalized Quadratic Assignment Problem (GQAP), with an emphasis on modelling and solving a practical problem, namely an examination timetabling problem. We found that the proposed algorithm is able to perform better than the standard SA algorithm does.
Keywords
education; quadratic programming; search problems; simulated annealing; GQAP; GRASP; QAPLIB test problems; SA-TS; examination timetabling problem; generalized quadratic assignment problem; good quality solutions; greedy randomized adaptive search procedure; hybrid metaheuristics; hybrid simulated annealing and tabu search algorithm; standard SA algorithm; Benchmark testing; Educational institutions; Heuristic algorithms; Linear programming; Simulated annealing; Standards;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation Science and Engineering (CASE), 2014 IEEE International Conference on
Conference_Location
Taipei
Type
conf
DOI
10.1109/CoASE.2014.6899314
Filename
6899314
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