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An effective two-stage stochastic multi-trip location-transportation model with social concerns in relief supply chains

Moreno, Alfredo; Alem, Douglas; Ferreira, Deisemara; Clark, Alistair

Authors

Alfredo Moreno

Douglas Alem

Deisemara Ferreira

Alistair Clark



Abstract

© 2018 Elsevier B.V. The distribution of emergency aid from warehouses to relief centers to satisfy the needs of the victims in the aftermath of a disaster is a complex problem because it requires a rapid response to human suffering when resources are scarce amidst great uncertainty. In order to provide an effective response and use resources efficiently, this paper presents a novel model to optimize location, transportation, and fleet sizing decisions. In contrast with existing models, vehicles can be reused for multiple trips within micro-periods (blocks of hours) and/or over periods (days). Uncertainty regarding demand, incoming supply, and availability of routes is modeled via a finite set of scenarios, using two-stage stochastic programs. ‘Deprivation costs’ are used to represent social concerns and minimized via two objective functions. Mathematical programming based heuristics are devised to enable good-quality solutions within reasonable computing time. Experimental results based on data from the disastrous 2011 floods and landslides in the Serrana Region of Rio de Janeiro, Brazil, show that the model's novel characteristics help get aid faster to victims and naturally enforce fairness in its distribution to disaster areas in a humanitarian spirit.

Journal Article Type Article
Acceptance Date Feb 8, 2018
Publication Date Sep 16, 2018
Deposit Date Feb 9, 2018
Publicly Available Date Sep 17, 2020
Journal European Journal of Operational Research
Print ISSN 0377-2217
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 269
Issue 3
Pages 1050-1071
DOI https://doi.org/10.1016/j.ejor.2018.02.022
Keywords operational research in disaster relief, location-transportation and fleet sizing, multiple trips, deprivation costs, MIP heuristics
Public URL https://uwe-repository.worktribe.com/output/871444
Publisher URL https://doi.org/10.1016/j.ejor.2018.02.022
Contract Date Feb 9, 2018

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