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Siting and Sizing of Facilities under Probabilistic Demands

Author

Listed:
  • Luís M. Fernandes

    (Instituto Politécnico de Tomar and Instituto de Telecomunicações)

  • Joaquim J. Júdice

    (Universidade de Coimbra and Instituto de Telecomunicações)

  • Hanif D. Sherali

    (Virginia Polytechnic Institute & State University)

  • António P. Antunes

    (Universidade de Coimbra)

Abstract

In this paper a discrete location model for non-essential service facilities planning is described, which seeks the number, location, and size of facilities, that maximizes the total expected demand attracted by the facilities. It is assumed that the demand for service is sensitive to the distance from facilities and to their size. It is also assumed that facilities must satisfy a threshold level of demand (facilities are not economically viable below that level). A Mixed-Integer Nonlinear Programming (MINLP) model is proposed for this problem. A branch-and-bound algorithm is designed for solving this MINLP and its convergence to a global minimum is established. A finite procedure is also introduced to find a feasible solution for the MINLP that reduces the overall search in the binary tree generated by the branch-and-bound algorithm. Some numerical results using a GAMS/MINOS implementation of the algorithm are reported to illustrate its efficacy and efficiency in practice.

Suggested Citation

  • Luís M. Fernandes & Joaquim J. Júdice & Hanif D. Sherali & António P. Antunes, 2013. "Siting and Sizing of Facilities under Probabilistic Demands," Journal of Optimization Theory and Applications, Springer, vol. 158(1), pages 284-304, July.
    • Handle: RePEc:spr:joptap:v:158:y:2013:i:1:d:10.1007_s10957-010-9789-8
    DOI: 10.1007/s10957-010-9789-8
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    References listed on IDEAS

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