Determining the number of facilities for large-scale emergency

Authors:
Lingpeng Meng;Qin Ma;Chuanfeng Han;Qidi Wu
Affiliations:
School of Electronics and Information, Tongji University, No. 4800, Cao'an Road, Shanghai, 201804, China;Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, University of Georgia, Davison Life Sciences Bldg. A110, 120 E Green St., Athens, GA 30602-7229, USA;Institute of Urban Construction and Emergency Management, Tongji University, No. 1239, Siping Road, Shanghai, 200092, China;School of Electronics and Information, Tongji University, No. 4800, Cao'an Road, Shanghai, 201804, China
Venue:
International Journal of Computing Science and Mathematics
Year:
2013

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Abstract

Classical facility location models like the maximum covering location model implicitly assume that the number of facilities is given exogenously. However, the tremendous magnitude and low frequency of large-scale emergencies make it difficult to apply the above assumption simply. This paper developed a greedy clustering method aiming to identify suitable number of large-scale emergency facilities, taking into account of the distinct attributes of each demand area and the required response quality. An illustrative example is given to show the effectiveness and efficiency of the proposed method.