RT Journal Article
T1 A Mathematical Pre-Disaster Model with Uncertainty and Multiple Criteria for Facility Location and Network Fortification
A1 Monzón, Julia
A1 Liberatore, Federico
A1 Vitoriano Villanueva, Begoña
AB 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.
PB MDPI
SN 2227-7390
YR 2020
FD 2020-04-03
LK https://hdl.handle.net/20.500.14352/7547
UL https://hdl.handle.net/20.500.14352/7547
LA eng
NO Monzón, J., Liberatore, F., Vitoriano, B.: A Mathematical Pre-Disaster Model with Uncertainty and Multiple Criteria for Facility Location and Network Fortification. Mathematics. 8, 529 (2020). https://doi.org/10.3390/math8040529
NO European Commission
NO Ministerio de Ciencia, Innovación y Universidades (España)
NO Universidad Complutense de Madrid
DS Docta Complutense
RD 12 abr 2025