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A mathematical pre-disaster model with uncertainty and multiple criteria for facility location and network fortification

Monzón, Julia, Liberatore, Federico and Vitoriano, Begoña 2020. A mathematical pre-disaster model with uncertainty and multiple criteria for facility location and network fortification. Mathematics 8 (4) , 529. 10.3390/math8040529

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Abstract

Disasters have catastrophic effects on the affected population, especially in developing and underdeveloped countries. Humanitarian Logistics models can help decision-makers to efficiently and effectively warehouse and distribute emergency goods to the affected population, to reduce casualties and suffering. However, poor planning and structural damage to the transportation infrastructure could hamper these efforts and, eventually, make it impossible to reach all the affected demand centers. In this paper, a pre-disaster Humanitarian Logistics model is presented that jointly optimizes the prepositioning of aid distribution centers and the strengthening of road sections to ensure that as much affected population as possible can efficiently get help. The model is stochastic in nature and considers that the demand in the centers affected by the disaster and the state of the transportation network are random. Uncertainty is represented through scenarios representing possible disasters. The methodology is applied to a real-world case study based on the 2018 storm system that hit the Nampula Province in Mozambique.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: MDPI
ISSN: 2227-7390
Date of First Compliant Deposit: 7 April 2020
Date of Acceptance: 22 March 2020
Last Modified: 07 Apr 2020 09:45
URI: http://orca.cf.ac.uk/id/eprint/130864

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