caa a22 4500 445840005 CHVBK 20180317145341.0 cr unu---uuuuu 170323e20111201xx s 000 0 eng 10.1007/s00186-011-0363-4 doi (NATIONALLICENCE)springer-10.1007/s00186-011-0363-4 Covering models and optimization techniques for emergency response facility location and planning: a review [Elektronische Daten] [Xueping Li, Zhaoxia Zhao, Xiaoyan Zhu, Tami Wyatt] 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. Springer-Verlag, 2011 Emergency facility location nationallicence Modeling and optimization nationallicence Mathematical modeling nationallicence Covering model nationallicence Genetic algorithm nationallicence Tabu search nationallicence Simulation nationallicence Li Xueping Department of Industrial and Information Engineering, University of Tennessee, 416 East Stadium Hall, 37919, Knoxville, TN, USA aut Zhao Zhaoxia Department of Industrial and Information Engineering, University of Tennessee, 416 East Stadium Hall, 37919, Knoxville, TN, USA aut Zhu Xiaoyan Department of Industrial and Information Engineering, University of Tennessee, 416 East Stadium Hall, 37919, Knoxville, TN, USA aut Wyatt Tami College of Nursing, University of Tennessee, 200 Volunteer Boulevard, 37996-4180, Knoxville, TN, USA aut Mathematical Methods of Operations Research Springer-Verlag 74/3(2011-12-01), 281-310 1432-2994 74:3<281 2011 74 186 https://doi.org/10.1007/s00186-011-0363-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00186-011-0363-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Li Xueping Department of Industrial and Information Engineering, University of Tennessee, 416 East Stadium Hall, 37919, Knoxville, TN, USA aut NATIONALLICENCE 700 1- Zhao Zhaoxia Department of Industrial and Information Engineering, University of Tennessee, 416 East Stadium Hall, 37919, Knoxville, TN, USA aut NATIONALLICENCE 700 1- Zhu Xiaoyan Department of Industrial and Information Engineering, University of Tennessee, 416 East Stadium Hall, 37919, Knoxville, TN, USA aut NATIONALLICENCE 700 1- Wyatt Tami College of Nursing, University of Tennessee, 200 Volunteer Boulevard, 37996-4180, Knoxville, TN, USA aut NATIONALLICENCE 773 0- Mathematical Methods of Operations Research Springer-Verlag 74/3(2011-12-01), 281-310 1432-2994 74:3<281 2011 74 186 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer