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
Link To Document :
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