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A Capacitated Location-Allocation Model for Flood Disaster Service Operations with Border Crossing Passages and Probabilistic Demand Locations

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  • Seyed Ali Mirzapour
  • Kuan Yew Wong
  • Kannan Govindan

Abstract

Potential consequences of flood disasters, including severe loss of life and property, induce emergency managers to find the appropriate locations of relief rooms to evacuate people from the origin points to a safe place in order to lessen the possible impact of flood disasters. In this research, a p-center location problem is considered in order to determine the locations of some relief rooms in a city and their corresponding allocation clusters. This study presents a mixed integer nonlinear programming model of a capacitated facility location-allocation problem which simultaneously considers the probabilistic distribution of demand locations and a fixed line barrier in a region. The proposed model aims at minimizing the maximum expected weighted distance from the relief rooms to all the demand regions in order to decrease the evacuation time of people from the affected areas before flood occurrence. A real-world case study has been carried out to examine the effectiveness and applicability of the proposed model.

Suggested Citation

  • Seyed Ali Mirzapour & Kuan Yew Wong & Kannan Govindan, 2013. "A Capacitated Location-Allocation Model for Flood Disaster Service Operations with Border Crossing Passages and Probabilistic Demand Locations," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-11, December.
  • Handle: RePEc:hin:jnlmpe:507953
    DOI: 10.1155/2013/507953
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    Cited by:

    1. Shaw, Lipika & Das, Soumen Kumar & Roy, Sankar Kumar, 2022. "Location-allocation problem for resource distribution under uncertainty in disaster relief operations," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    2. Wapee Manopiniwes & Takashi Irohara, 2021. "Optimization model for temporary depot problem in flood disaster response," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(2), pages 1743-1763, January.

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