A two-stage stochastic programming framework for transportation planning in disaster response

Barbarosoğlu, Gülay; Arda, Yasemin

doi:10.1057/palgrave.jors.2601652

Cited by 596 publications

(296 citation statements)

References 13 publications

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“…Only a small number of demand points for distribution is usually considered in the literature. Vitoriano et al (2010) treat 9 demand points (PODs), while 6 and 30 PODs are treated by Barbarosoglu and Arda (2004) and Rawls and Turnquist (2010) respectively. The solution time of the model increases with the number of PODs, but in a relatively mild manner.…”

Section: Computational Efficiencymentioning

confidence: 99%

A three-stage stochastic facility routing model for disaster response planning

Rennemo

Rø

Hvattum

et al. 2014

Transportation Research Part E: Logistics and Transportation Re

168

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This paper presents a humanitarian logistics decision model to be used in the event of a disaster. The operations under consideration span from opening of local distribution facilities and initial allocation of supplies, to last mile distribution of aid. A mathematical model is developed aiming to enable efficient decision making, maximizing the utility of distribution of aid amongst beneficiaries. This model is formulated as a three-stage mixed-integer stochastic programming model to account for the difficulty in predicting the outcome of a disaster.Accessibility of new information implies initiation of distinct operations in the humanitarian supply chain, be it facility location and supply allocation, or last mile distribution planning and execution. The realized level of demand, in addition to the transportation resources available to the decision maker for execution of last mile aid distribution and the state of the infrastructure, are parameters treated as random due to uncertainty.An assessment of the applicability and validity of the stochastic program is made through extensive computational testing based on several test instances. The results show that instances of considerable size are challenging to solve due to the complexity of the stochastic programming model but, still, optimal solutions may be found within a reasonable time frame. Moreover, findings prove the value of the stochastic programming model to be significant as compared with a deterministic expected value approach. Finally, the model is also applied to a case study based on the earthquake that hit Haiti in January of 2010, showing how it could be used in a realistic operation framework.

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Section: Computational Efficiencymentioning

confidence: 99%

A three-stage stochastic facility routing model for disaster response planning

Rennemo

Rø

Hvattum

et al. 2014

Transportation Research Part E: Logistics and Transportation Re

168

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“…Haghani and Oh (1996) used a deterministic multicommodity, multimodal network flow model to plan disaster relief. Barbarosoglu and Arda (2004) extended this approach to include random arc capacity, supply, and demand. They formulated the problem as a two-stage stochastic program and used data from the August 1999 earthquake in Marmara, Turkey.…”

Section: Disaster Planning and Responsementioning

confidence: 99%

A Survey of Operations Research Models and Applications in Homeland Security

2006

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Operations research has had a long and distinguished history of work in emergency preparedness and response, airline security, transportation of hazardous materials, and threat and vulnerability analysis. Since the attacks of September 11, 2001 and the formation of the US Department of Homeland Security, these topics have been gathered under the broad umbrella of homeland security. In addition, other areas of OR applications in homeland security are evolving, such as border and port security, cyber security, and critical infrastructure protection. The opportunities for operations researchers to contribute to homeland security remain numerous.

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“…One group of these studies, such as Barbasuglu [18,19] and Haghani and OH [20,21], concentrated on a routing problem and distribution of emergency goods. These studies were to minimize time and cost of transportation and assumed that several relief goods from several depot were shipped by heterogeneous vehicles to the a ected areas.…”

Section: Related Workmentioning

confidence: 99%

“…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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A two-stage stochastic programming framework for transportation planning in disaster response

Cited by 596 publications

References 13 publications

A three-stage stochastic facility routing model for disaster response planning

A three-stage stochastic facility routing model for disaster response planning

A Survey of Operations Research Models and Applications in Homeland Security

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

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