A multi-objective stochastic programming model to configure a sustainable humanitarian logistics considering deprivation cost and patient severity

As the occurrence of disasters has increased frequently and has resulted in growing concern about their adverse effects on the environment, Sustainable Humanitarian Logistics (SHL) has received great attention recently. SHL aims to reduce disaster damages in an environmentally-friendly manner in the...

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Veröffentlicht in:	Annals of operations research Jg. 319; H. 1; S. 1265 - 1300
Hauptverfasser:	Jamali, Amir, Ranjbar, Amirhossein, Heydari, Jafar, Nayeri, Sina
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2022 Springer Springer Nature B.V
Schlagworte:	Business and Management Combinatorics Costs Deprivation Disaster management Disaster relief Earthquake damage Environmental effects Goal programming Humanitarian aid Humanitarianism Integer programming Iran Logistics Mixed integer Operations research Operations Research/Decision Theory S.I.: Design and Management of Humanitarian Supply Chains Sensitivity analysis Social factors Stochastic models Stochastic programming Sustainability Sustainable development Theory of Computation Iran Humanitarian logistics Sustainable disaster management Stochastic multi-objective optimization Deprivation cost
ISSN:	0254-5330, 1572-9338
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Abstract	As the occurrence of disasters has increased frequently and has resulted in growing concern about their adverse effects on the environment, Sustainable Humanitarian Logistics (SHL) has received great attention recently. SHL aims to reduce disaster damages in an environmentally-friendly manner in the shortest possible time. The terms including ‘environmentally-friendly’ and ‘shortest possible time’ refer to the environmental and social aspects of sustainability. This research proposes a stochastic multi-objective mixed-integer programming model to configure an SHL network during the response phase. Having compared to the research literature, this is the first study that considers economic, social, and environmental aspects of sustainability by incorporating relief cost, deprivation cost, and carbon emissions, respectively. Then, the improved multi-choice goal programming approach is applied to solve the proposed multi-objective model. To indicate the validity of the proposed model, an earthquake that occurred in a region of Kermanshah, Iran, in 2017 is investigated as a real case study. Finally, sensitivity analysis is performed and several managerial and theoretical insights are provided. The results show that exerting environmental issues in humanitarian logistics does not necessarily increase the relief costs, but can be in contrast with the social aspect. Furthermore, a minor increase in the budget of the preparedness phase drastically decreases the response costs.
AbstractList	As the occurrence of disasters has increased frequently and has resulted in growing concern about their adverse effects on the environment, Sustainable Humanitarian Logistics (SHL) has received great attention recently. SHL aims to reduce disaster damages in an environmentally-friendly manner in the shortest possible time. The terms including ‘environmentally-friendly’ and ‘shortest possible time’ refer to the environmental and social aspects of sustainability. This research proposes a stochastic multi-objective mixed-integer programming model to configure an SHL network during the response phase. Having compared to the research literature, this is the first study that considers economic, social, and environmental aspects of sustainability by incorporating relief cost, deprivation cost, and carbon emissions, respectively. Then, the improved multi-choice goal programming approach is applied to solve the proposed multi-objective model. To indicate the validity of the proposed model, an earthquake that occurred in a region of Kermanshah, Iran, in 2017 is investigated as a real case study. Finally, sensitivity analysis is performed and several managerial and theoretical insights are provided. The results show that exerting environmental issues in humanitarian logistics does not necessarily increase the relief costs, but can be in contrast with the social aspect. Furthermore, a minor increase in the budget of the preparedness phase drastically decreases the response costs.
Audience	Academic
Author	Jamali, Amir Nayeri, Sina Heydari, Jafar Ranjbar, Amirhossein
Author_xml	– sequence: 1 givenname: Amir surname: Jamali fullname: Jamali, Amir organization: School of Industrial Engineering, College of Engineering, University of Tehran – sequence: 2 givenname: Amirhossein surname: Ranjbar fullname: Ranjbar, Amirhossein organization: School of Industrial Engineering, College of Engineering, University of Tehran – sequence: 3 givenname: Jafar orcidid: 0000-0001-6728-5950 surname: Heydari fullname: Heydari, Jafar email: J.Heydari@ut.ac.ir organization: School of Industrial Engineering, College of Engineering, University of Tehran – sequence: 4 givenname: Sina surname: Nayeri fullname: Nayeri, Sina organization: School of Industrial Engineering, College of Engineering, University of Tehran
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Keywords	Humanitarian logistics Sustainable disaster management Stochastic multi-objective optimization Deprivation cost
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SubjectTerms	Business and Management Combinatorics Costs Deprivation Disaster management Disaster relief Earthquake damage Environmental effects Goal programming Humanitarian aid Humanitarianism Integer programming Iran Logistics Mixed integer Operations research Operations Research/Decision Theory S.I.: Design and Management of Humanitarian Supply Chains Sensitivity analysis Social factors Stochastic models Stochastic programming Sustainability Sustainable development Theory of Computation
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Title	A multi-objective stochastic programming model to configure a sustainable humanitarian logistics considering deprivation cost and patient severity
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