Cooperative maximal covering models for humanitarian relief chain management

Li, Xueping; Ramshani, Mohammad; Huang, Yu Tsung

doi:10.1016/j.cie.2018.04.004

Cited by 41 publications

(28 citation statements)

References 25 publications

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“…In this study, each affected area is devoted to the nearest distribution center, and inventory is distributed among demand points fairly and equitably by presenting a new constraint. Balcik and Beamon (2008), Mete and Zabinsky (2010), Irohara, Kuo and Leung (2013), Rath and Gutjahr (2014), Rath and Gutjahr (2014), Bozorgi-Amiri and Khorsi (2016), Caunhye et al (2016), Rezaei-Malek et al (2016a), Rezaei-Malek et al (2016b, Condeixa et al (2017), Elçi and Noyan (2018), Li, Ramshani and Huang (2018), Tavana et al (2018), Torabi et al (2018) , Cotes and Cantillo (2019), Hu and Dong (2019), Noyan, Meraklı and Küçükyavuz (2019), Wang and Nie (2019), Chen ( 2020) focused on pre-disaster location and procurement problems as well as a distribution problem. Balcik and Beamon (2008) determined distribution centers location, the amounts of relief commodities stored at each center, and the share of each center in satisfying demands considering a criticality weight for each relief item, different coverage levels for each commodity with different priorities , and satisfying the larger amount of demand at the lower coverage level, in a network including a set of distribution centers and a demand point.…”

Section: Literature Reviewmentioning

confidence: 98%

“…In this study, the equitable distribution of goods along with determining transportation routes and required vehicles were examined. Li et al (2018) presented a cooperative maximal covering model where relief items were prioritized. In the studies conducted by Rath et al (2014), Bozorgi-Amiri and Khorsi (2016), Torabi et al (2018), Cotes and Cantillo (2019), and Hu and Dong (2019), a multi-sourcing problem 1 was used to procure relief items.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Location-Procurement-Distribution Model Combined with Data Envelopment Analysis Model under a Multi-period Environment and Gradual Budget Injection for Humanitarian Relief Supply Chains

Fazli¹

2021

Preprint

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Humanmade or natural catastrophes such as droughts, floods, earthquakes, storms, coups, economic and political crises, wars, and so forth impact various areas of the world annually. Furthermore, the lack of adequate preparations and proper coping against them causes nations to suffer heavy losses and casualties, which are sometimes irrecoverable. Consequently, as an essential activity in crisis management, humanitarian relief logistics has been of particular importance and has taken a good deal of notice at the international level during recent years. Aid facilities location and the storage of necessary commodities before a disaster and the proper distribution of relief commodities among demand points following a disaster are critical logistical strategies to improve performance and reduce latency when responding to a given disaster. In this regard, this study presents a stochastic multi-objective mixed-integer non-linear programming model in a two-level network that includes warehouses and affected areas. The model aims at minimizing total social costs, which include the expense of founding warehouses, the expense of procuring commodities, and deprivation cost, as well as maximizing fulfilled demands and warehouses utility. In this study, several pre-disaster periods, a limited budget for establishing warehouses and procuring relief commodities with their gradual injection into the system, the time value of money, various criteria for evaluating warehouses, the risk of disruption in warehouses and transportation networks, and heterogeneous warehouses are considered. The maximization of warehouses utility is done according to a data envelopment analysis model. Moreover, a multi-objective fuzzy programming model called the weighted max-min model is applied to solve the proposed model. Ultimately, the outcomes of the evaluation and validation of the proposed model show its appropriate and efficient performance.

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Section: Literature Reviewmentioning

confidence: 98%

Section: Literature Reviewmentioning

confidence: 99%

A Location-Procurement-Distribution Model Combined with Data Envelopment Analysis Model under a Multi-period Environment and Gradual Budget Injection for Humanitarian Relief Supply Chains

Fazli¹

2021

Preprint

View full text Add to dashboard Cite

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“…Pasandideh et al [32] proposed a multiobjective hub MCLP to simultaneously maximize both network reliability and commodity flow. Taking into account the uncertainty related to the impact of disasters, Li et al [33] formulated a cooperative MCLP for the design of a humanitarian relief logistics network. Paul et al [34] formulated an improved biobjective MCLP for the network redesign of a large-scale emergency response system.…”

Section: Maximal Covering Location Problemmentioning

confidence: 99%

Solving a Real-World Urban Postal Service System Redesign Problem

Sun

Solvang

et al. 2021

Scientific Programming

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Due to recent technological advancements, more diversified customer demand, and increasingly harder competition, traditional postal service systems have experienced significant changes all over the world. In Norway, through a strategic reform called post-in-shop, undertaken in 2013, most postal services are now provided at postal service counters located in retailer stores in order to improve accessibility, operational efficiency, and cost-effectiveness. This has led to a complex decision-making problem for the redesign of urban postal service networks across the country. In this paper, a two-stage method is proposed to solve a real-world urban postal service network redesign problem. First, two location models are employed to determine the optimal locations of postal service counters. In the second stage, a simulation model is built to evaluate the urban postal service system with different location and demand allocation plans under a realistic and stochastic environment. Among other insights, our results show that the proposed two-stage method can be used to effectively improve the accessibility of postal service networks by making optimal location-allocation decisions.

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“…In addition, a few studies try to explain the forces associated with coordination. Lack of trust among NGOs is the main barrier to coordination [67]. The stability of partnerships can be destroyed by "free-riding" behavior [65].…”

Section: Ngos In Humanitarian Supply Chainsmentioning

confidence: 99%

Horizontal Coordination of I-LNGOs in the Humanitarian Supply Chain: An Evolutionary Game Approach

2020

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Disasters accompanied by heavy casualties and huge economic losses directly result in the disruption or delay of economic development. Considering the urgent need for reducing losses and accelerating the process of social recovery, international nongovernment organizations (INGOs) and local NGOs (LNGOs) with different resource endowments should achieve organizational coordination to improve the relief efficiency and sustainability of the humanitarian supply chain. Due to conflicting interests and expectations, this coordination is hard to achieve. In this study, we first establish an evolutionary game model between INGOs and LNGOs to determine the influencing factors and explore the interaction of NGOs in a dynamic way. Our results show that: (1) coordination by resource sharing can improve the sustainability of the humanitarian supply chain; (2) coordination willingness is affected by the behavior of other players, which can nevertheless achieve equilibrium under certain conditions; and (3) the important factors and optimal strategies of players are highlighted in the dynamic model. This study provides several insights into the theory of organizational coordination in the humanitarian supply chain regarding sustainability.

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Cooperative maximal covering models for humanitarian relief chain management

Cited by 41 publications

References 25 publications

A Location-Procurement-Distribution Model Combined with Data Envelopment Analysis Model under a Multi-period Environment and Gradual Budget Injection for Humanitarian Relief Supply Chains

A Location-Procurement-Distribution Model Combined with Data Envelopment Analysis Model under a Multi-period Environment and Gradual Budget Injection for Humanitarian Relief Supply Chains

Solving a Real-World Urban Postal Service System Redesign Problem

Horizontal Coordination of I-LNGOs in the Humanitarian Supply Chain: An Evolutionary Game Approach

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