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Humanitarian supply chain: models and solution methods

Abstract

In this research project, we will study three operations planning problems that arise in the humanitarian logistics context: (i) a dynamic network-flow problem in which the uncertainty regarding the victims' needs is modeled according to the robust optimization perspective; (ii) a location-distribution problem with fleet sizing decisions and deprivation costs; and (iii) a supply chain design problem. The proposed problems involve the treatment of diverse uncertainty parameters, such as demand, supply, costs, among others, which will be modeled via stochastic programming and/or robust optimization. The main motivation in proposing models and solution methods for these specific problems relies on the lack of scientific investigation about them and on the computational difficulty for solving practical instances. The objectives of this project involve contextualizing the problems, formulating the corresponding optimization models, solving them, and analyzing the numerical results from the disaster management viewpoint. The results of this project will be disseminated in scientific conferences and submitted to specialized journals. (AU)

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VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)

Scientific publications (5)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
MORENO, ALFREDO; MUNARI, PEDRO; ALEM, DOUGLAS. Decomposition-based algorithms for the crew scheduling and routing problem in road restoration. Computers & Operations Research, v. 119, JUL 2020. Web of Science Citations: 0.
MUNARI, PEDRO; MORENO, ALFREDO; DE LA VEGA, JONATHAN; ALEM, DOUGLAS; GONDZIO, JACEK; MORABITO, REINALDO. The Robust Vehicle Routing Problem with Time Windows: Compact Formulation and Branch-Price-and-Cut Method. TRANSPORTATION SCIENCE, v. 53, n. 4, p. 1043-1066, JUL-AUG 2019. Web of Science Citations: 0.
MORENO, ALFREDO; MUNARI, PEDRO; ALEM, DOUGLAS. A branch-and-Benders-cut algorithm for the Crew Scheduling and Routing Problem in road restoration. European Journal of Operational Research, v. 275, n. 1, p. 16-34, MAY 16 2019. Web of Science Citations: 3.
MORENO, ALFREDO; ALEM, DOUGLAS; FERREIRA, DEISEMARA; CLARK, ALISTAIR. An effective two-stage stochastic multi-trip location-transportation model with social concerns in relief supply chains. European Journal of Operational Research, v. 269, n. 3, p. 1050-1071, SEP 16 2018. Web of Science Citations: 9.
ALEM, DOUGLAS; CURCIO, EDUARDO; AMORIM, PEDRO; ALMADA-LOBO, BERNARDO. A computational study of the general lot-sizing and scheduling model under demand uncertainty via robust and stochastic approaches. Computers & Operations Research, v. 90, p. 125-141, FEB 2018. Web of Science Citations: 7.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.