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Decomposition-based solution methods for logistics network planning

Grant number: 19/25504-8
Support Opportunities:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): September 01, 2020
Effective date (End): May 31, 2021
Field of knowledge:Engineering - Production Engineering - Operational Research
Principal Investigator:Reinaldo Morabito Neto
Grantee:Aura Maria Jalal Osorio
Supervisor: Raf Jans
Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
Research place: École des Hautes Études Commerciales (HEC Montréal), Canada  
Associated to the scholarship:18/09563-1 - Optimization models and solution methods for distribution network planning: a case study in the pharmaceutical sector, BP.DR


This research project addresses a logistics network planning problem, that integrates essential activities in the supply chain management, namely facility location and transportation planning. Practical features are considered to make the problem more realistic such as security measures, different freight types, and taxes levied on the supply chain. In Brazil, there is a value-added tax which affects all the stages of supply chain and the logistics network design, and whose rate depends on the origin-destination. In this way, the total value of the tax on distribution operations depends on the DC locations. We propose a multiproduct, multiperiod, and multimodal mathematical model integrating network design and distribution planning decisions, such as product flow, transportation modes, type freight shipping, fleet sizing, and escorting services for high value cargo, in order to minimize logistics and tax costs. In addition, we develop a robust optimization model for dealing with uncertainty in demands and transportation costs. We established a partnership with a pharmaceutical multinational that has operations in Brazil and we have already collected real data from this company to build different sets of instances. Small instances of the deterministic formulation and its robust counterpart can be solved to optimally by general purpose software, like CPLEX. However, high quality solutions cannot be found within reasonable times using these software for large instances. Hence, the objective of this research project is to propose, for both deterministic and robust problem, solution methods based in decomposition or/and matheuristic algorithms. Also, practical features will be considered to make the addressed problem more realistic, so the proposed methods can be an interesting contribution to the literature and useful for decision makers in practice. This research will be conducted under the supervision of professors Raf Jans and Yossiri Adulyasak, full Professors of the Department of Logistics and Operations Management, HEC-Montréal, who are experts in optimization and solution methods. (AU)

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