| Grant number: | 18/09563-1 |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| Start date: | August 01, 2018 |
| End date: | February 28, 2022 |
| Field of knowledge: | Engineering - Production Engineering - Operational Research |
| Principal Investigator: | Reinaldo Morabito Neto |
| Grantee: | Aura Maria Jalal Osorio |
| Host Institution: | Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil |
| Associated scholarship(s): | 19/25504-8 - Decomposition-based solution methods for logistics network planning, BE.EP.DR |
Abstract Distribution network planning involves decisions such as location-allocation, inventory management and transportation. These decisions belong to different decision levels, but are interconnected. Hence, they must be integrated in order to achieve an adequate service level and a minimum cost in network operations. In this doctoral project, we pretend to study strategic-tactical and tactical-operational planning for distribution networks, focusing on pharmaceutical distribution networks. The objective is to identify the most relevant decisions at each hierarchical level, to understand how these decisions interact with each other, and to develop optimization models based on mathematical programming that represent the problem. In the modeling would be considered characteristics that have not been contemplated so far in the literature, such as transportation and storage of multiple products under different temperature conditions, safety measures in cargo transportation and inventory location along the distribution network. We pretend to incorporate in the modeling tax aspects that are specific to the distribution networks in Brazil such as Tax of Circulation of Goods and Services (ICMS). ICMS tax is little explored in the literature and is relevant for the decision-making of companies. To solve the proposed models, we pretend to investigate solution methods exploring specific characteristics of the problem such as decomposition based approaches and/or mathematical programming based heuristics. For the development of this research, we pretend to carry out a real case study. We have already established a partnership with a pharmaceutical multinational that has operations in Brazil. (AU) | |
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