Research on Multiobjective Location of Urban Emergency Logistics under Major Emergencies

After the outbreak of major emergencies, the scheduling of emergency supplies is the key to the emergency rescue work, and the establishment of appropriate emergency logistics centers plays a crucial supporting role. In order to deal with the problem of emergency facility location and material distr...

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Vydané v:Mathematical problems in engineering Ročník 2021; s. 1 - 12
Hlavní autori: Wang, Hongchun, Ma, Xinying
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Hindawi 2021
John Wiley & Sons, Inc
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Abstract After the outbreak of major emergencies, the scheduling of emergency supplies is the key to the emergency rescue work, and the establishment of appropriate emergency logistics centers plays a crucial supporting role. In order to deal with the problem of emergency facility location and material distribution in urban emergency logistics system, this paper establishes a dual objective mixed integer nonlinear programming (MINLP) model with the objective of minimizing the emergency rescue time and maximizing the satisfaction rate of emergency material demand, designs a genetic algorithm to solve the emergency logistics location and allocation model, and obtains the Pareto optimal solution set of the model. Finally, a case study of COVID-19 epidemic in Beijing-Tianjin-Hebei region was carried out to verify the feasibility and effectiveness of the model and algorithm in the actual application, which can provide reference and suggestions for the location and material distribution of urban emergency logistics centers.
AbstractList After the outbreak of major emergencies, the scheduling of emergency supplies is the key to the emergency rescue work, and the establishment of appropriate emergency logistics centers plays a crucial supporting role. In order to deal with the problem of emergency facility location and material distribution in urban emergency logistics system, this paper establishes a dual objective mixed integer nonlinear programming (MINLP) model with the objective of minimizing the emergency rescue time and maximizing the satisfaction rate of emergency material demand, designs a genetic algorithm to solve the emergency logistics location and allocation model, and obtains the Pareto optimal solution set of the model. Finally, a case study of COVID-19 epidemic in Beijing-Tianjin-Hebei region was carried out to verify the feasibility and effectiveness of the model and algorithm in the actual application, which can provide reference and suggestions for the location and material distribution of urban emergency logistics centers.
Author Ma, Xinying
Wang, Hongchun
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Cites_doi 10.1515/jhsem-2013-0107
10.1007/s00170-013-5379-x
10.1016/j.ejor.2005.03.077
10.1287/msom.2013.0460
10.1016/s0925-7535(00)00021-7
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Copyright Copyright © 2021 Hongchun Wang and Xinying Ma.
Copyright © 2021 Hongchun Wang and Xinying Ma. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms Coronaviruses
COVID-19
Decision making
Disasters
Disease transmission
Earthquakes
Emergencies
Fuzzy logic
Genetic algorithms
Linear programming
Logistics
Mathematical problems
Mathematical programming
Mixed integer
Multiple objective analysis
Network management systems
Nonlinear programming
Optimization
Public health
Rescue operations
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