A credibility-based multi-objective temporary logistics hub location-allocation model for relief supply and distribution under uncertainty

Disaster response operations revolve around uncertainties. While uncertainties arising due to randomness can be avoided for post-disaster location problem, those arising because of impreciseness may persist long after the disaster's occurrence. Despite the uncertainties and lack of sufficient i...

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Vydáno v:Socio-economic planning sciences Ročník 70; s. 100727
Hlavní autoři: Maharjan, Rajali, Hanaoka, Shinya
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Elsevier Ltd 01.06.2020
Elsevier Science Ltd
Témata:
Allocation
Attainment
Credibility
Decision making
Disaster relief
Disasters
Emergency preparedness
Epistemic uncertainty
Facility location-allocation problem
Fuzzy chance-constrained programming
Fuzzy logic
Humanitarian supply chain
Logistics
Multi-objective optimization
Objectives
Randomness
Sensitivity analysis
Subjectivity
Temporary logistics hub
Uncertainty
Temporary logistics hub
Fuzzy chance-constrained programming
Epistemic uncertainty
Multi-objective optimization
Humanitarian supply chain
Facility location-allocation problem
ISSN:0038-0121, 1873-6041
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Shrnutí:Disaster response operations revolve around uncertainties. While uncertainties arising due to randomness can be avoided for post-disaster location problem, those arising because of impreciseness may persist long after the disaster's occurrence. Despite the uncertainties and lack of sufficient information about the extent of the damage, disaster response facilities must be established quickly after the occurrence of the disaster. Moreover, the decisions of whether to open, where to locate, and when to open disaster response facilities are based on the amount and quality of information available during the decision-making period. To address these issues, we develop a multi-objective location-allocation model for relief supply and distribution that accounts for the imprecise and time-varying nature of different parameters and time-varying coverage, while also accommodating the subjective attributes necessary to enable establishment and operation of the temporary logistics hubs (TLHs). A credibility-based fuzzy chance-constrained programming model is employed to account for the impreciseness inherent in predicting parameter values during disaster response. The results show where, when, and how many TLHs to open and how to allocate relief supplies. Meanwhile, the sensitivity analysis provides a broader understanding of the impact of limiting the number of TLHs as well as the confidence level and the spread of the symmetric triangular fuzzy numbers on the attainment of the model objectives. •Disaster response operations are complicated because of uncertain and time-varying nature of parameters.•The uncertainty during disaster response is often epistemic which arises due to impreciseness.•We develop a multi-objective location model for relief supply and distribution.•Our model accounts for the epistemic uncertainty in demand, costs, and available relief.•A credibility-based fuzzy chance-constrained programming model is employed to account for epistemic uncertainty.
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ISSN:0038-0121
1873-6041
DOI:10.1016/j.seps.2019.07.003