Covering models and optimization techniques for emergency response facility location and planning: a review |
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Authors: | Xueping Li Zhaoxia Zhao Xiaoyan Zhu Tami Wyatt |
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Institution: | (1) GeoDa Center for Geospatial Analysis and Computation, School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287-5302, USA |
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Abstract: | With emergencies being, unfortunately, part of our lives, it is crucial to efficiently plan and allocate emergency response
facilities that deliver effective and timely relief to people most in need. Emergency Medical Services (EMS) allocation problems
deal with locating EMS facilities among potential sites to provide efficient and effective services over a wide area with
spatially distributed demands. It is often problematic due to the intrinsic complexity of these problems. This paper reviews
covering models and optimization techniques for emergency response facility location and planning in the literature from the
past few decades, while emphasizing recent developments. We introduce several typical covering models and their extensions
ordered from simple to complex, including Location Set Covering Problem (LSCP), Maximal Covering Location Problem (MCLP),
Double Standard Model (DSM), Maximum Expected Covering Location Problem (MEXCLP), and Maximum Availability Location Problem
(MALP) models. In addition, recent developments on hypercube queuing models, dynamic allocation models, gradual covering models,
and cooperative covering models are also presented in this paper. The corresponding optimization techniques to solve these
models, including heuristic algorithms, simulation, and exact methods, are summarized. |
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Keywords: | |
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