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Strategies for solving large location-allocation problems by heuristic methods


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  • P J Densham
  • G Rushton
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    Solution techniques for location-allocation problems usually are not a part of microcomputer-based geoprocessmg systems because of the large volumes of data to process and store and the complexity of algorithms. In this paper, it is shown that processing costs for the most accurate, heuristic, location-allocation algorithm can be drastically reduced by exploiting the spatial structure of location-allocation problems. The strategies used, preprocessing interpoint distance data as both candidate and demand strings, and use of them to update an allocation table, allow the solution of large problems (3000 nodes) in a microcomputer-based, interactive decisionmaking environment. Moreover, these strategies yield solution times which increase approximately linearly with problem size. Tests on four network problems validate these claims.

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    Bibliographic Info

    Article provided by Pion Ltd, London in its journal Environment and Planning A.

    Volume (Year): 24 (1992)
    Issue (Month): 2 (February)
    Pages: 289-304

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    Handle: RePEc:pio:envira:v:24:y:1992:i:2:p:289-304

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    Cited by:
    1. Miquel Carreras & Daniel Serra, 1997. "On optimal location with treshold requirements," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra 220, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Rosing, K. E. & ReVelle, C. S. & Schilling, D. A., 1999. "A gamma heuristic for the p-median problem," European Journal of Operational Research, Elsevier, Elsevier, vol. 117(3), pages 522-532, September.
    3. K.E. Rosing & C.S. ReVelle, 1997. "Heuristic Concentration and Tabu Search: A Nose to Nose Comparison," Tinbergen Institute Discussion Papers, Tinbergen Institute 97-058/3, Tinbergen Institute.
    4. Marianov, Vladimir & Serra, Daniel & ReVelle, Charles, 1999. "Location of hubs in a competitive environment," European Journal of Operational Research, Elsevier, Elsevier, vol. 114(2), pages 363-371, April.
    5. Rosing, K. E. & ReVelle, C. S., 1997. "Heuristic concentration: Two stage solution construction," European Journal of Operational Research, Elsevier, Elsevier, vol. 97(1), pages 75-86, February.
    6. Rosing, K. E. & ReVelle, C. S. & Rolland, E. & Schilling, D. A. & Current, J. R., 1998. "Heuristic concentration and Tabu search: A head to head comparison," European Journal of Operational Research, Elsevier, Elsevier, vol. 104(1), pages 93-99, January.


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