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Applying simulated annealing to location-planning models

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Abstract

Simulated annealing is a computational approach that simulates an annealing schedule used in producing glass and metals. Originally developed by Metropolis et al. in 1953, it has since been applied to a number of integer programming problems, including the p-median location-allocation problem. However, previously reported results by Golden and Skiscim in 1986 were less than encouraging. This article addresses the design of a simulated-annealing approach for the p-median and maximal covering location problems. This design has produced very good solutions in modest amounts of computer time. Comparisons with an interchange heuristic demonstrate that simulated annealing has potential as a solution technique for solving location-planning problems and further research should be encouraged.

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Authors and Affiliations

  1. Australian Housing and Urban Research Institute, Queensland University of Technology, 4000, Brisbane, Queensland, Australia

    Alan T. Murray

  2. National Center for Geographic Information and Analysis, University of California at Santa Barbara, 93106, Santa Barbara, CA, USA

    Richard L. Church

  3. the Department of Geography, University of California at Santa Barbara, 93106, Santa Barbara, CA, USA

    Richard L. Church

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  1. Alan T. Murray
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  2. Richard L. Church
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Murray, A.T., Church, R.L. Applying simulated annealing to location-planning models. J Heuristics 2, 31–53 (1996). https://doi.org/10.1007/BF00226292

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