Robust reliable humanitarian relief network design: an integration of shelter and supply facility location

Yahyaei, Mohsen; Bozorgi-Amiri, Ali

doi:10.1007/s10479-018-2758-6

Cited by 78 publications

(49 citation statements)

References 29 publications

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“…Other studies have considered coping with the risk of disruption in distribution centers after disasters while optimizing the location of two facilities with different reliability. These facilities include secure infrastructures and facilities that may be disrupted to ensure the smooth distribution of post-disaster relief supplies [26]. However, the issue of considering shelters that can provide different types of services to meet the needs of different asylum seekers has been largely ignored [27].…”

Section: Literature Reviewmentioning

confidence: 99%

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Multi-Criteria Location Model of Emergency Shelters in Humanitarian Logistics

2020

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Natural disasters can cause serious casualties and economic losses, and emergency shelters are effective measures to reduce disaster risks and protect lives. At present, the location models of refuge facilities often ignore the diversion of shelter from the perspective of humanitarian logistics and the needs of victims. Such models also seldom consider the impact of the pre-storage of relief materials on the location of shelters. In this study, on the basis of the different needs of disaster victims, shelters are divided into two types—basic life and psychological medical service guarantees. While considering the full coverage of shelter needs, capacities, and budget constraints, the shelter distance, the optimized distribution of refugees, and the pre-stock quantity of goods are optimized. The facility service quality is optimized on the basis of qualitative factors. This study proposes a multi-standard constrained site selection model to optimize the pre-disaster shelter site-allocation problem. The model is helpful for decision makers to influence shelter siting and victims’ allocating process through their expertise and to obtain a solution that compromises multiple objectives. In this study, several basic cases are generated from the actual data of certain areas in Sichuan Province, a disaster-prone region in China, to verify the effectiveness of the model.

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Section: Literature Reviewmentioning

confidence: 99%

“…Candidate sites should avoid fault lines, and slopes should not exceed 7%, preferably between 2% and 4% [22]. Concurrently, in rainy areas, the existence of vegetation helps consolidate the soil and prevent debris flow [19,21,26]. Electricity is an important guarantee for maintaining daily living.…”

Section: Criteria For Choosing Emergency Sheltersmentioning

confidence: 99%

Multi-Criteria Location Model of Emergency Shelters in Humanitarian Logistics

2020

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“…Albareda-Sambola et al [12] introduced the facility capacity into a reliable facility location problem with unsplittable demands. Yahyaei and Bozorgi-Amiri [13] studied the reliable network design problem for humanitarian relief, and they proposed a robust linear programming model to deal with the uncertainty in this problem. Afify et al [14] proposed an evolutionary learning technique to solve the reliable pmedian problem and the reliable uncapacitated facility location problem under the assumption that facilities have heterogeneous failure probabilities.…”

Section: Literature Reviewmentioning

confidence: 99%

“…(7)-(11) are the classical constraints for the maximal flow problem. Constraints (12) and (13) confirm that each demand point is allocated only one backup and one primary facility. Constraint (14) confirms that the primary facility and the backup facility must be different.…”

Section: Model Representationmentioning

confidence: 99%

“…To investigate the impact of the links to be reinforced, we delved into the solutions for G � 500. For a given ω, let us keep the primary facility and the (11)(12) 0.93 -- (11)(12)(13)(14) 0.05 0.79 76 backup facility that is allocated to each demand point unchanged and then compare the reachability guarantee before and after reinforcing a link. Table 5 lists these comparisons of the reachability guarantee when ω � 0.1, 0.5, 0.7.…”

Section: Effects Of Reinforced Linksmentioning

confidence: 99%

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Optimization Model Based on Reachability Guarantee for Emergency Facility Location and Link Reinforcement

Liu

2020

Journal of Advanced Transportation

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The reasonable location of emergency facilities plays an important role in both predisaster service and postdisaster relief. Moreover, damage to the transportation network often affects the accessibility of demand points, which can seriously hamper timely rescue operations. Reasonable location of emergency facilities and reinforcement of fragile roads are two important strategies to improve the reachability of demand points. In this paper, we proposed a biobjective optimization model to determine locations of emergency facilities and links to be reinforced given a limited budget. Each demand point is allocated a primary facility and a backup facility, the former can provides normal service, and the latter is prepared for postdisaster relief. One goal of the model is to minimize the operating cost of normal services, and another goal is to maximize the reachability guarantee of demand points. The novelty and contribution of this paper are that we defined the reachability by introducing damage tolerance instead of link failure probability. Based on this, we defined the reachability guarantee to deal with the worst scenario of disasters. By embedding the max-flow problem of the reachability guarantee into the emergency facility location problem, the locations of emergency facilities and links to be reinforced can be determined simultaneously. The methodology is applied to a simplified Sioux Falls transportation network. Results such as the trade-off curve of two goals, budget efficiency, and the effect of reinforcement demonstrated the effectiveness of the model.

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Shelter Location-Allocation Problem with Vulnerabilities of Network and Disruption of Shelter During the Response Phase of Disaster

Hansuwa¹,

Mohan²,

Ganesan³

2021

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

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In this paper, we define and formulate the shelter location-allocation problem considering both the network vulnerability of the affected area and the shelter's disruption during the disaster management's response phase. We capture the vulnerability metric using the traveling cost and location vulnerability for shelter disruption using the shelter's operating cost. We formulate the problem as a mixed-integer linear programming (MILP) model and present an evacueeallocation plan considering vulnerable network connectivities between the populated areas and the shelter locations. We finally apply and solve the problem using real-life case data obtained during the Nepal earthquake in 2015 and compare our models with Rahman's same data [10]. We demonstrate using the case example the usefulness of our modelling approach and show that we can achieve better results compared to a simulation study.

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Robust reliable humanitarian relief network design: an integration of shelter and supply facility location

Cited by 78 publications

References 29 publications

Multi-Criteria Location Model of Emergency Shelters in Humanitarian Logistics

Multi-Criteria Location Model of Emergency Shelters in Humanitarian Logistics

Optimization Model Based on Reachability Guarantee for Emergency Facility Location and Link Reinforcement

Shelter Location-Allocation Problem with Vulnerabilities of Network and Disruption of Shelter During the Response Phase of Disaster

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