Abstract
People are always threatened by natural disasters which usually cause significant losses. Therefore, planning for confronting such situations is a vast dilemma. In this paper, a general model is proposed to address the uncertain demand of disaster-stricken areas. Demand from injured people relates to the vulnerability of regions that depends on the quality of buildings and severity of damage. In the studied problem, the commodities collected from relief centers, donations and storage warehouses are distributed to the shelters. It aims at minimizing the total cost, and unfulfilled demand and maximizing the coverage and accessibility of relief centers. The LP-metric approach is utilized to solve the multi-objective model, and a scenario-based optimization is used to incorporate the uncertainty in the proposed model. Moreover, an LP–GA method is proposed for optimizing large-scale instances. Several problems in different scales are solved to show its flexibility and time-efficiency. Finally, a case study of an earthquake disaster in Amol city in Iran is presented. The obtained results suggest better service in the distressed urban areas.
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Hasan Molladavoodi, Mohammad Mahdi Paydar, Abdul Sattar Safaei certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent licensing arrangements) or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.
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Molladavoodi, H., Paydar, M.M. & Safaei, A.S. A disaster relief operations management model: a hybrid LP–GA approach. Neural Comput & Applic 32, 1173–1194 (2020). https://doi.org/10.1007/s00521-018-3762-0
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DOI: https://doi.org/10.1007/s00521-018-3762-0