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A more efficient heuristic for solving largep-median problems

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Papers in Regional Science

Abstract

The Teitz and Bart (1968) vertex substitution heuristic is more robust than competing algorithms and yields solutions with properties that are necessary, but not sufficient, for a global optimum solution. All documented implementations of this algorithm, however, use a naive spatial search procedure, whereas a more informed spatial search procedure, requiring considerably less computation to solve any given problem, is possible. An algorithm incorporating this new search procedure, called the global/regional interchange algorithm, is described. As problem size increases, proportionally larger reductions in processing costs occur.

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References

  • Densham, P. J., and Rushton, G. 1991.Designing and implementing strategies for solving large location-allocation problems by heuristic methods. Santa Barbara, California: National Center for Geographic Information and Analysis, Technical Report 91-10.

    Google Scholar 

  • Densham, P. J., and Rushton, G. 1992. Strategies for solving large location-allocation problems by heuristic methods.Environment and Planning A 24: 289–304.

    Google Scholar 

  • Feldman, E., Lehrer, F. A., and Ray, T. L. 1966. Warehouse locations under continuous economies of scale.Management Science 12: 670–84.

    Google Scholar 

  • Goodchild, M. F., and Noronha, V. 1983.Location-allocation for small computers. Iowa City: Department of Geography, The University of Iowa, Monograph No. 8.

    Google Scholar 

  • Hillsman, E. L. 1980.Heuristic solutions to location-allocation problems: a users' guide to ALLOC IV, V, and VI. Iowa City: Department of Geography, The University of Iowa, Monograph No. 7.

    Google Scholar 

  • Hillsman, E. L. 1984. Thep-median structure as a unified linear model for location-allocation analysis.Environment and Planning A 16: 305–18.

    Google Scholar 

  • Kuehn, A. A., and Hamburger, M. J. 1963. A heuristic program for locating warehouses.Management Science 9: 643–66.

    Google Scholar 

  • Maranzana, F. E. 1964. On the location of supply points to minimize transport costs.Operational Research Quarterly 15: 261–70.

    Google Scholar 

  • Park, S. B. 1989. Performance of successively complex rules for locational decision-making.Annals of Operations Research 18: 323–44.

    Google Scholar 

  • Rosing, K. E., Hillsman, E. L., and Rosing-Vogelaar, H. 1979. A note comparing optimal and heuristic solutions to thep-median problem.Geographical Analysis 11: 86–89.

    Google Scholar 

  • Rushton, G. 1987. Selecting the objective function in location-allocation analyses. InSpatial analysis and location-allocation models, eds. A. Ghosh and G. Rushton, New York: Van Nostrand Reinhold, pp. 345–64.

    Google Scholar 

  • Teitz, M. B., and Bart, P. 1968. Heuristic methods for estimating the generalized vertex median of a weighted graph.Operations Research 16: 955–61.

    Google Scholar 

  • Willer, D. J. 1990.A spatial decision support system for bank location; a case study. Santa Barbara, California: National Center for Geographic Information and Analysis, Technical Report 90-9.

    Google Scholar 

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Densham, P.J., Rushton, G. A more efficient heuristic for solving largep-median problems. Papers in Regional Science 71, 307–329 (1992). https://doi.org/10.1007/BF01434270

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