A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains

Cao, Cejun; Liu, Yang; Tang, Ou; Gao, Xuehong

doi:10.1016/j.ijpe.2021.108081

Cited by 79 publications

(46 citation statements)

References 66 publications

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“…The aftermath of any disaster necessitates an immediate supply of emergency RM to minimize human sufferings (Dubey & Gunasekaran, 2016 ; Wang et al, 2016b ; Behl & Dutta, 2020a ; Behl & Dutta, 2020b ; Shafiq & Soratana, 2020 ; Cao et al, 2021 ). Because of various trade-offs and uncertainty in the decision-making environment (Maiyar & Thakkar, 2020 ), it is always challenging to achieve this goal during execution (Dubey et al, 2019a ; Özdamar et al, 2004 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Because of various trade-offs and uncertainty in the decision-making environment (Maiyar & Thakkar, 2020 ), it is always challenging to achieve this goal during execution (Dubey et al, 2019a ; Özdamar et al, 2004 ). Authors study the humanitarian aid delivery problem under uncertainty in demand and cost (Faiz & Vogiatzis, 2020 ; Liu & Nagurney, 2013 ; Sun et al, 2018 ; Tofighi et al, 2016 ; Zokaee et al, 2016 ), demand and carbon price (Rezaee et al, 2017 ), estimated arrival times, travel time and cost, transportation plan risk (Zheng & Ling, 2013 ), the response time (Bastian et al, 2016 ), loading–unloading time (Abazari et al, 2020 ), inventory amounts (Cao et al, 2021 ), etc. Majorly, the concepts of two-stage stochastic programming (Grass & Fischer, 2016 ).…”

Section: Literature Reviewmentioning

confidence: 99%

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A probabilistic fuzzy goal programming model for managing the supply of emergency relief materials

2021

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The post-disaster humanitarian logistic operations deal with the supply of emergency relief materials to mitigate damages in the affected areas. Immediately after the disaster, it is challenging to estimate the demand for emergency relief materials. As a result, the demand for such materials at the point of demand and the corresponding transportation costs for the entire supply chain network becomes uncertain. This paper proposes a new probabilistic fuzzy goal programming model for making decisions to manage the post-disaster supply of emergency relief materials. A suggested procedure converts the proposed model to its deterministic equivalent when the demands for the relief materials follow uniform distributions. We implement the differential evolution, a metaheuristic technique, for analyzing demand satisfaction for relief materials under various scenarios. A case example based on the Nepal Earthquake in 2015 demonstrates the usefulness of the proposed approach. The solution of the model will help the Disaster Management Agency coordinate with the humanitarian organizations and foreign countries to provide the required emergency relief materials so that an adequate level of supply can be assured to the affected areas with the least possible transportation cost.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A probabilistic fuzzy goal programming model for managing the supply of emergency relief materials

2021

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“…After large-scale disasters such as earthquakes, floods, tropical storms, and nuclear leaks, many people are affected and injured severely. In the event of such a disaster, rapid and effective responses to a disaster are required to relieve the detrimental situation [8,16,33,35,37,38,69]. Among them, the most expeditious response is to help all those injured people who require medical attendance through life-saving operations [7].…”

Section: Introductionmentioning

confidence: 99%

A note on the warehouse location problem with data contamination

Gao

Cui²

2021

RAIRO-Oper. Res.

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To determine the optimal warehouse location, it is usually assumed that the collected data are uncontaminated. However, this assumption can be easily violated due to the uncertain environment and human error in disaster response, which results in the biased estimation of the optimal warehouse location. In this study, we investigate this possibility by examining these estimation effects on the warehouse location determination. Considering different distances, we propose the corresponding estimation methods for remedying the difficulties associated with data contamination to determine the warehouse location. Although data can be contaminated in the event of a disaster, the findings of the study is much broader and applicable to any situation where the outliers exist. Through the simulations and illustrative examples, we show that solving the problem with center of gravity lead to biased solutions even if only one outlier exists in the data. Compared with the center of gravity, the proposed methods are quite efficient and outperform the existing methods when the data contamination is involved.

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“…Meanwhile, the total return of the society will become smaller, which is not aligned with the regulatory expected revenue and damages the interests of regulatory authorities. According to García-Pérez et al [7] and Cao et al [8], sustainability can be seen as the result of the coordination of interests among multiple stakeholders. It is almost impossible to achieve the sustainable operation of P2P lending if the conflict of interest among P2P lending participants is not balanced [9].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Game Analysis of Three Players on Behavioural Strategy of P2P Lending Participants: A Sustainable Operations Perspective

et al. 2021

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In China, most of peer-to-peer (P2P) lending platforms do not possess operational sustainability due to excessive defaults. To address this problem, the conflict of interests among P2P lending participants is discussed using a stakeholder approach. An evolutionary game model (EGM) of three players is developed to analyse the interactions among regulatory authorities, P2P lending platforms, and borrowers. Then, the asymptotic of the equilibrium and evolutionary stability strategies of the EGM are analysed. Results indicate that either the P2P lending platforms or borrowers will choose “noncompliant operation” or “default” strategies from a short-term perspective, and the strict supervision of the P2P lending platform in the short term is necessary for the sustainable operation of the platform. When supervision is intensified in the early stage and regulatory pressure becomes a normal state, P2P lending platforms and borrowers will actively select “compliant operation” and “repayment” strategies even if there is a lack of regulation in the future. Meanwhile, the behavioural strategies of P2P lending participants can be changed to conform to the sustainability of P2P lending by reducing the costs of strict supervision and increasing the damage caused by general supervision, reward and punishment coefficient for P2P lending platforms, repayment incentives of borrowers, and defaulting opportunity costs. Finally, suggestions for regulating the behaviours of P2P lending participants and promoting sustainability of P2P lending industry are discussed.

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A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains

Cited by 79 publications

References 66 publications

A probabilistic fuzzy goal programming model for managing the supply of emergency relief materials

A probabilistic fuzzy goal programming model for managing the supply of emergency relief materials

A note on the warehouse location problem with data contamination

Evolutionary Game Analysis of Three Players on Behavioural Strategy of P2P Lending Participants: A Sustainable Operations Perspective

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