Humanitarian supply chain: models and solution methods

• Grant number: 15/26453-7
• Support Opportunities: Regular Research Grants
• Start date: March 01, 2016
• End date: February 28, 2018
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Douglas José Alem Junior
• Grantee: Douglas José Alem Junior
• Host Institution: Centro de Ciências em Gestão e Tecnologia (CCGT). Universidade Federal de São Carlos (UFSCAR). Campus de Sorocaba. Sorocaba , SP, Brazil

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)

Scientific publications

(6)

(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; 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. (15/26453-7)

MORENO, ALFREDO; ALEM, DOUGLAS; GENDREAU, MICHEL; MUNARI, PEDRO. The heterogeneous multicrew scheduling and routing problem in road restoration. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, v. 141, p. 35-pg., 2020-11-01. (15/26453-7, 16/23366-9)

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. (15/26453-7, 13/08303-2)

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. (16/15966-6, 15/26453-7, 16/23366-9)

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. (16/23366-9, 13/07375-0, 15/14582-7, 14/50228-0, 15/26453-7, 16/01860-1)

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. (16/23366-9, 16/15966-6, 15/26453-7)