• 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