Inventory relocation for overlapping disaster settings in humanitarian operations

Rottkemper, Beate; Fischer, Kathrin; Blecken, Alexander; Danne, Christoph

doi:10.1007/s00291-011-0260-5

Cited by 82 publications

(48 citation statements)

References 40 publications

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“…It involves decisions regarding the reallocation of stocks and transport of relief items in an uncertain environment (Rawls and Turnquist, 2010;Charles, 2010;Rottkemper et al, 2011). It is this limitation of the existing design models of HSCs that we intend to address in this research work.…”

Section: Designing Humanitarian Supply Chainsmentioning

confidence: 97%

A decision support system for robust humanitarian facility location

Flórez

Lauras

Okongwu

et al. 2015

Engineering Applications of Artificial Intelligence

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a b s t r a c tEach year, more than 400 natural disasters hit the world. To be more responsive, humanitarians organize stocks of relief items. It is an issue to know the quantity of items to be stored and where they should be positioned. Many authors have tried to address this issue both in industrial and humanitarian environments. However, humanitarian supply chains today do not perform correctly, particularly as regards resilience and efficiency. This is mainly due to the fact that when a disaster occurs, some hazards can strongly impact the network by destroying some resources or collapsing infrastructure. The expected performance of the relief response is consequently strongly decreased. The problem statement of our research work consists in proposing a decision-making support model in artificial intelligence dedicated to the humanitarian world and capable of designing a coherent network that is still able to adequately manage the response to a disaster despite failures or inadequacies of infrastructure and potential resources. This contribution is defined through a Stochastic Multi-Scenarios Program as a core and a set of extensions. A real-life application case based on the design of a humanitarian supply chain in Peru is developed in order to highlight the benefits and limits of the proposition.

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Section: Designing Humanitarian Supply Chainsmentioning

confidence: 97%

A decision support system for robust humanitarian facility location

Flórez

Lauras

Okongwu

et al. 2015

Engineering Applications of Artificial Intelligence

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“…At the strategic level, prepositioning relief goods in the region near some likely-to-happen locations according to historical data is discussed in [4] and [5]. Balcik Sheu [12] addresses quick response to urgent relief by a hybrid fuzzy clustering-optimization approach involving two recursive mechanisms: disaster-affected area grouping and relief co-distribution.…”

Section: Literature Reviewmentioning

confidence: 99%

Logistics orchestration modeling and evaluation for humanitarian relief

Lau

et al. 2012

Proceedings of 2012 IEEE International Conference on Service Operations and Logistics, and Informatics

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“…There are a number of articles focusing on different subtopics of aid chain flows. Some investigate the material procurement related issues (e.g., Campbell and Jones, 2011;Chang et al, 2010;Ertem et al, 2012); while others study inventory management and material distribution (e.g., Taskin and Lodree, 2011;Rottkemper et al, 2011).…”

Section: Flows and Distributionmentioning

confidence: 99%