International disaster relief planning with fuzzy credibility

Adıvar, Burcu; Mert, Ali

doi:10.1007/s10700-010-9088-8

Cited by 34 publications

(10 citation statements)

References 22 publications

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“…Related to the topics studied in this work, Arora, Raghu, and Vinze (2010) focused on the allocation of medical aid for emergencies considering the coordination between regions, whereas Adıvar and Mert (2010) aimed to coordinate international relief items using fuzzy logic to provide a collectiondistribution plan. Altay (2013) developed a model to allocate response personnel, facilities, supplies and equipment with two alternative objective functions; to minimise deployment time or minimise maximum response time.…”

Section: Resource Management Among Multiple Actorsmentioning

confidence: 99%

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

Rodríguez-Espíndola

Albores

Brewster

2018

European Journal of Operational Research

166

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The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency.Consequently, successful operations rely heavily on the collaboration of different organisations.Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence.This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities.The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities.Keywords: Humanitarian logistics, multiple objective programming, OR in disaster relief, disaster preparedness. THEORETICAL FRAMEWORK2.

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Section: Resource Management Among Multiple Actorsmentioning

confidence: 99%

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

Rodríguez-Espíndola

Albores

Brewster

2018

European Journal of Operational Research

166

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“…When a disaster occurs, aid from donor countries and international organizations is sent to the disaster stricken country. For the effective management of these relief goods Adıvar and Mert [52] and Camacho-Vallejo et al [53] suggested models with the objectives of minimizing total response time for delivering and cost for procurement. Details of all the models discussed above for network design and disaster relief distribution in HSC are given in Table 2.…”

Section: Network Design and Relief Distribution In Humanitarian Supplmentioning

confidence: 99%

Mathematical Models in Humanitarian Supply Chain Management: A Systematic Literature Review

Habib

Lee

Memon

2016

Mathematical Problems in Engineering

106

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In the past decade the humanitarian supply chain (HSC) has attracted the attention of researchers due to the increasing frequency of disasters. The uncertainty in time, location, and severity of disaster during predisaster phase and poor conditions of available infrastructure during postdisaster phase make HSC operations difficult to handle. In order to overcome the difficulties during these phases, we need to assure that HSC operations are designed in an efficient manner to minimize human and economic losses. In the recent times, several mathematical optimization techniques and algorithms have been developed to increase the efficiency of HSC operations. These techniques and algorithms developed for the field of HSC motivate the need of a systematic literature review. Owing to the importance of mathematical modelling techniques, this paper presents the review of the mathematical contributions made in the last decade in the field of HSC. A systematic literature review methodology is used for this paper due to its transparent procedure. There are two objectives of this study: the first one is to conduct an up-to-date survey of mathematical models developed in HSC area and the second one is to highlight the potential research areas which require attention of the researchers.

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“…A multi-mode transportation eet (i.e., ground, marine, and air) made the model more e cient and exible in the real world. Therefore, Barbasoglu [19], Rennemo et al [24], Hu [25], Naja et al [26], Adivar and Mert [27], and Ozdamar [28] followed this issue in separate studies.…”

Section: Related Workmentioning

confidence: 99%

A cluster-based emergency vehicle routing problem in disaster with reliability

et al. 2017

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Abstract. In the event of natural disasters, relief distribution is the most challenging problem in emergency transportation. What is important in response to disaster is victims' relief in disaster areas with the quick distribution of vital commodity. In this regard, damage to infrastructure (e.g., roads) can make trouble in designing a distribution network. Therefore, this paper considers a problem using a three-stage approach. In the rst stage, pre-processing of model inputs is done through an Arti cial Neural Fuzzy Inference System (ANFIS) followed by investigating the safest route for each cluster using decision-making techniques and graph theory. In the second stage, a heterogeneous multi-depot multimode vehicle routing problem is formulated for minimizing the transportation time and maximizing the reliability. Finally, since the routing problem is NP-hard, 2 multi-objective meta-heuristic algorithms, namely, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Fire y Algorithm (MOFA), are proposed to obtain the optimal solution and their performances are compared through a set of randomly generated test problems. The results show that for this routing problem, the MOFF gives better solutions than NSGA-II does, and it performs well in terms of accuracy and solution time.

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International disaster relief planning with fuzzy credibility

Cited by 34 publications

References 22 publications

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

Mathematical Models in Humanitarian Supply Chain Management: A Systematic Literature Review

A cluster-based emergency vehicle routing problem in disaster with reliability

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