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A graph-pair representation and MIP-model-based heuristic for the unequal-area facility layout problem

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  • Bozer, Yavuz A.
  • Wang, Chi-Tai
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    Abstract

    Owing to its theoretical as well as practical significance, the facility layout problem with unequal-area departments has been studied for several decades, with a wide range of heuristic and a few exact solution procedures developed by numerous researchers. In one of the exact procedures, the facility layout problem is formulated as a mixed-integer programming (MIP) model in which binary (0/1) variables are used to prevent departments from overlapping with one another. Obtaining an optimal solution to the MIP model is difficult, and currently only problems with a limited number of departments can be solved to optimality. Motivated by this situation, we developed a heuristic procedure which uses a “graph pair” to determine and manipulate the relative location of the departments in the layout. The graph-pair representation technique essentially eliminates the binary variables in the MIP model, which allows the heuristic to solve a large number of linear programming models to construct and improve the layout in a comparatively short period of time. The search procedure to improve the layout is driven by a simulated annealing algorithm. The effectiveness of the proposed graph-pair heuristic is demonstrated by comparing the results with those reported in recent papers. Possible extensions to the graph-pair representation technique are discussed at the end of the paper.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 218 (2012)
    Issue (Month): 2 ()
    Pages: 382-391

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    Handle: RePEc:eee:ejores:v:218:y:2012:i:2:p:382-391

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Facilities planning and design; Simulated annealing; Graph-pair representation; Heuristics; Integer programming;

    References

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    1. Komarudin & Wong, Kuan Yew, 2010. "Applying Ant System for solving Unequal Area Facility Layout Problems," European Journal of Operational Research, Elsevier, vol. 202(3), pages 730-746, May.
    2. Gordon C. Armour & Elwood S. Buffa, 1963. "A Heuristic Algorithm and Simulation Approach to Relative Location of Facilities," Management Science, INFORMS, vol. 9(2), pages 294-309, January.
    3. van Camp, Drew J. & Carter, Michael W. & Vannelli, Anthony, 1992. "A nonlinear optimization approach for solving facility layout problems," European Journal of Operational Research, Elsevier, vol. 57(2), pages 174-189, March.
    4. Scholz, Daniel & Petrick, Anita & Domschke, Wolfgang, 2009. "STaTS: A Slicing Tree and Tabu Search based heuristic for the unequal area facility layout problem," European Journal of Operational Research, Elsevier, vol. 197(1), pages 166-178, August.
    5. Scholz, Daniel & Petrick, Anita & Domschke, Wolfgang, 2009. "STaTS: A Slicing Tree and Tabu Search based heuristic for the unequal area facility layout problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 39430, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Heragu, Sunderesh S. & Kusiak, Andrew, 1991. "Efficient models for the facility layout problem," European Journal of Operational Research, Elsevier, vol. 53(1), pages 1-13, July.
    7. Koulamas, C & Antony, SR & Jaen, R, 1994. "A survey of simulated annealing applications to operations research problems," Omega, Elsevier, vol. 22(1), pages 41-56, January.
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    Cited by:
    1. Kulturel-Konak, Sadan, 2012. "A linear programming embedded probabilistic tabu search for the unequal-area facility layout problem with flexible bays," European Journal of Operational Research, Elsevier, vol. 223(3), pages 614-625.

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