Models, solutions and enabling technologies in humanitarian logistics

Özdamar, Linet; Ertem, Mustafa Alp

doi:10.1016/j.ejor.2014.11.030

Cited by 344 publications

(178 citation statements)

References 85 publications

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“…This paper will not review all decision models for disaster management and emergencies, but rather will focus on the quantitative management of uncertainty in emergency logistics planning in disaster relief, considering only recent research on scenario-based stochastic programming approaches in transportation and distribution relief within network flows. The reader who is interested in wider surveys of the application of quantitative models and operational research to humanitarian logistics can consult Altay and Green Galindo and Batta (2013); Leiras et al (2014) and Özdamar and Ertem (2015) amongst others. Two-stage stochastic programming with recourse models have been successfully used in humanitarian logistics and disaster management as they allow the modeller to represent pre-and post-event phases together via first-and second-stage decision variables.…”

Section: Related Literaturementioning

confidence: 99%

Stochastic network models for logistics planning in disaster relief

Alem

Clark

Moreno

2016

European Journal of Operational Research

228

102

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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.

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Section: Related Literaturementioning

confidence: 99%

Stochastic network models for logistics planning in disaster relief

Alem

Clark

Moreno

2016

European Journal of Operational Research

228

102

View full text Add to dashboard Cite

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“…In DOM, many models are NP-hard Caunhye et al 2012); therefore, the algorithms for solving them are intensively studied (e.g., Hoyos et al 2015;Özdamar and Ertem 2015;Yuan and Wang 2009). For example, Wei and Kumar (2007) proposed an antcolony optimization method to solve the multi-commodity and vehicle dispatch problems that arise in disaster relief scenarios.…”

Section: Humanitarian or Disaster Operations Managementmentioning

confidence: 99%

Emergency logistics for wildfire suppression based on forecasted disaster evolution

2017

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This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces).

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“…To coordinate relief organizations, various structures (Raju & Becker, 2013;Raju & Niekerk, 2013), mechanisms (Balcik et al, 2010), and information technology-based platforms have been developed (Rossel et al, 2016;Poblet et al, 2017;Li et al, 2014). Balcik et al (2010), Schulz and Blecken (2010), Ozdamar and Ertem (2014), Caunhye et al (2012), and Altay and Green (2006) widely surveyed the existing literature regarding humanitarian disaster management. Balcik et al (2010) studied coordination in humanitarian relief chains and reviewed the challenges in coordinating relief organizations.…”

Section: Introductionmentioning

confidence: 99%

Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach

et al. 2017

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Abstract:Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a biobjective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic -constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation.

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Models, solutions and enabling technologies in humanitarian logistics

Cited by 344 publications

References 85 publications

Stochastic network models for logistics planning in disaster relief

Stochastic network models for logistics planning in disaster relief

Emergency logistics for wildfire suppression based on forecasted disaster evolution

Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach

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