Connecting a population dynamic model with a multi-period location-allocation problem for post-disaster relief operations

Christophe Duhamel (), Andréa Cynthia Santos (), Daniel Brasil (), Eric Châtelet () and Babiga Birregah ()
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Christophe Duhamel: LIMOS-UBP, UMR CNRS 6158, Université Blaise Pascal
Andréa Cynthia Santos: Université de Technologie de Troyes
Daniel Brasil: Université de Technologie de Troyes
Eric Châtelet: Université de Technologie de Troyes
Babiga Birregah: Université de Technologie de Troyes

Annals of Operations Research, 2016, vol. 247, issue 2, No 15, 693-713

Abstract: Abstract In this study, we propose a mathematical model and heuristics for solving a multi-period location-allocation problem in post-disaster operations, which takes into account the impact of distribution over the population. Logistics restrictions such as human and financial resources are considered. In addition, a brief review on resilience system models is provided, as well as their connection with quantitative models for post-disaster relief operations. In particular, we highlight how one can improve resilience by means of OR/MS strategies. Then, a simpler resilience schema is proposed, which better reflects an active system for providing humanitarian aid in post-disaster operations, similar to the model focused in this work. The proposed model is non-linear and solved by a decomposition approach: the master level problem is addressed by a non-linear solver, while the slave subproblem is treated as a black-box coupling heuristics and a Variable Neighborhood Descent local search. Computational experiments have been done using several scenarios, and real data from Belo Horizonte city in Brazil.

Keywords: Post-disaster response; Logistics; Location-allocation; Resilience; Optimization; Heuristics (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10479-015-2104-1

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