A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district

Ahmadi, Morteza; Seifi, Abbas; Tootooni, Behnam

doi:10.1016/j.tre.2015.01.008

Cited by 226 publications

(121 citation statements)

References 24 publications

Supporting

Mentioning

117

Contrasting

Unclassified

Order By: Relevance

“…The integration between location and routing in emergency logistics is also tackled in Rennemo et al (2014) and Ahmadi et al (2015). The former authors have developed a first multi-stage stochastic programming model to deal with a facility routing model in humanitarian logistics.…”

Section: Related Literaturementioning

confidence: 99%

“…The authors illustrated the outperformance of the model in comparison to deterministic approaches via the evaluation of both the expected value of perfect information and the value of stochastic solution. Ahmadi et al (2015) proposed a location-routing model under network failure, multiple uses of vehicles, and standard relief time. Network failure is modelled via a two-stage stochastic program with random travel time and analysed using a case study in the San Francisco district.…”

Section: Related Literaturementioning

confidence: 99%

See 1 more Smart Citation

Stochastic network models for logistics planning in disaster relief

Alem

Clark

Moreno

2016

European Journal of Operational Research

211

102

View full text Add to dashboard Cite

Emergency logistics in disasters is fraught with planning and operational challenges, such as uncertainty about the exact nature and magnitude of the disaster, a lack of reliable information about the location and needs of victims, possible random supplies and donations, precarious transport links, scarcity of resources, and so on. This paper develops a new two-stage stochastic network flow model to help decide how to rapidly supply humanitarian aid to victims of a disaster within this context. The model takes into account practical characteristics that have been neglected by the literature so far, such as budget allocation, fleet sizing of multiple types of vehicles, procurement, and varying lead times over a dynamic multiperiod horizon. Attempting to improve demand fulfillment policy, we present some extensions of the model via state-of-art risk measures, such as semideviation and conditional value-at-risk. A simple two-phase heuristic to solve the problem within a reasonable amount of computing time is also suggested.Numerical tests based on the floods and landslides in Rio de Janeiro state, Brazil, show that the model can help plan and organise relief to provide good service levels in most scenarios, and how this depends on the type of disaster and resources. Moreover, we demonstrate that our heuristic performs well for real and random instances.

show abstract

Section: Related Literaturementioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

Stochastic network models for logistics planning in disaster relief

Alem

Clark

Moreno

2016

European Journal of Operational Research

211

102

View full text Add to dashboard Cite

show abstract

“…In this work, we relax this assumption: any two customers from a disrupted facility can be reassigned to any two backup facilities. Some studies (Ahmadi et al, 2015;Rennemo et al, 2014;Balcik and Beamon, 2008;Ukkusuri and Yushimito, 2008) on disaster response in the humanitarian supply chains are also related to our research. These studies focused on the stocking and distribution of relief supplies considering road destruction; however, they assumed that facilities are always reliable.…”

Section: Literature Reviewmentioning

confidence: 95%

A metaheuristic approach to the reliable location routing problem under disruptions

Zhang

Wang

et al. 2015

Transportation Research Part E: Logistics and Transportation Re

View full text Add to dashboard Cite

“…In humanitarian transport, the initial response is received 3 days after the catastrophe. Governmental and non-governmental organizations must immediately estimate the situation and send emergency commodity from local stores to a ected points [5]. Relief operations include activities such as setting up emergency facilities, searching for survivors, providing health and medical aid, dispatching relief supplies, reassignment of victims, scheduling rescuers, and coordinating these activities between organizations [6].…”

Section: Introduction 1motivationmentioning

confidence: 99%

“…In the response phase, operational decisions on vehicle routing, sta and equipment, and distribution of emergency supplies to the disaster regions are made. Throughout the recovery phase, restoration of the a ected areas to the prior situations is the main activity of governmental and non-governmental organizations [5].…”

Section: Introduction 1motivationmentioning

confidence: 99%

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

et al. 2017

View full text Add to dashboard Cite

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.

show abstract

A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district

Cited by 226 publications

References 24 publications

Stochastic network models for logistics planning in disaster relief

Stochastic network models for logistics planning in disaster relief

A metaheuristic approach to the reliable location routing problem under disruptions

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

Contact Info

Product

Resources

About