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A Robust Site Selection Model under uncertainty for Special Hospital Wards in Hong Kong

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  • Mohammad Heydari
  • Yanan Fan
  • Kin Keung Lai

Abstract

This paper process two robust models for site selection problems for one of the major Hospitals in Hong Kong. Three parameters, namely, level of uncertainty, infeasibility tolerance as well as the level of reliability, are incorporated. Then, 2 kinds of uncertainty; that is, the symmetric and bounded uncertainties have been investigated. Therefore, the issue of scheduling under uncertainty has been considered wherein unknown problem factors could be illustrated via a given probability distribution function. In this regard, Lin, Janak, and Floudas (2004) introduced one of the newly developed strong optimisation protocols. Hence, computers as well as the chemical engineering [1069-1085] has been developed for considering uncertainty illustrated through a given probability distribution. Finally, our accurate optimisation protocol has been on the basis of a min-max framework and in a case of application to the (MILP) problems it produced a precise solution that has immunity to uncertain data.

Suggested Citation

  • Mohammad Heydari & Yanan Fan & Kin Keung Lai, 2023. "A Robust Site Selection Model under uncertainty for Special Hospital Wards in Hong Kong," Papers 2307.11508, arXiv.org.
  • Handle: RePEc:arx:papers:2307.11508
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    References listed on IDEAS

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    1. Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
    2. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    3. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    4. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
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