Reliable Transportation of Humanitarian Supplies in Disaster Response: Model and Heuristic

Hamedi, Masoud; Haghani, Ali; Yang, Saini

doi:10.1016/j.sbspro.2012.09.835

Cited by 56 publications

(31 citation statements)

References 6 publications

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“…Vitoriano et al [31] considered this necessity and presented a goal programming model with objectives such as reliability and possibility of ransack attribute, in which heterogeneous vehicles delivered one relief good from multiple depots to a ected areas. In recent years, Hemedi et al [32] based their model on the premise that there was the possibility of failure by minimizing the reliability cost of the model. This model was developed for a relief distribution problem with multiple depots.…”

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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Section: Related Workmentioning

confidence: 99%

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

et al. 2017

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“…Transportation infrastructure comprises all edges and nodes in the transportation network (i.e., roads, railroads, airports, ports) and all transportation modes that facilitate public and economic mass transits and long-distance traffic (Fletcher 2002, European Commission 2004. Exogenous uncertainty implies unclear states and conditions of any part of this infrastructure (Hamedi et al 2012). As most logistical operations within and across P-SCs depend on intact transportation infrastructure, states and conditions determine (to a certain degree) how robust, flexible, or resilient P-SCs can be (Madhusudan and Ganapathy 2011).…”

Section: Uncertainty In Ad Hoc Disaster Managementmentioning

confidence: 99%

A new focus on risk reduction: an ad hoc decision support system for humanitarian relief logistics

Schätter

Wiens

Schultmann

2015

Ecosyst Health Sustain

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Abstract. Particularly in the early phases of a disaster, logistical decisions are needed to be made quickly and under high pressure for the decision-makers, knowing that their decisions may have direct consequences on the affected society and all future decisions. Proactive risk reduction may be helpful in providing decisionmakers with optimal strategies in advance. However, disasters are characterized by severe uncertainty and complexity, limited knowledge about the causes of the disaster, and continuous change of the situation in unpredicted ways. Following these assumptions, we believe that adequate proactive risk reduction measures are not practical. We propose strengthening the focus on ad hoc decision support to capture information in almost real time and to process information efficiently to reveal uncertainties that had not been previously predicted. Therefore, we present an ad hoc decision support system that uses scenario techniques to capture uncertainty by future developments of a situation and an optimization model to compute promising decision options. By combining these aspects in a dynamic manner and integrating new information continuously, it can be ensured that a decision is always based on the best currently available and processed information. And finally, to identify a robust decision option that is provided as a decision recommendation to the decision-makers, methods of multi-attribute decision making (MADM) are applied. Our approach is illustrated for a facility location decision problem arising in humanitarian relief logistics where the objective is to identify robust locations for tent hospitals to serve injured people in the immediate aftermath of the Haiti Earthquake 2010.Key words: ad hoc decision support; humanitarian relief logistics; information and communication technology; multi-criteria decision analysis; public safety-critical supply chains; robustness; scenario techniques.Citation: Schätter, F., M. Wiens, and F. Schultmann. 2015. A new focus on risk reduction: an ad hoc decision support system for humanitarian relief logistics. Ecosystem Health and Sustainability 1(3):10. http://dx

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mentioning

confidence: 99%