| Grant number: | 16/23366-9 |
| Support Opportunities: | Regular Research Grants |
| Start date: | April 01, 2017 |
| End date: | March 31, 2019 |
| Field of knowledge: | Engineering - Production Engineering - Operational Research |
| Principal Investigator: | Pedro Augusto Munari Junior |
| Grantee: | Pedro Augusto Munari Junior |
| Host Institution: | Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil |
Abstract
Formulations and solution methods for vehicle routing problems have shown to be important to the decision-making process in logistic operations. Hence, the literature concerning this subject has been active for decades and reaches a large number of publications every year. The inventory routing problem (IRP) is an extension of the vehicle routing problem that has received great attention recently. This extension consists in incorporating inventory management decisions into the vehicle routing and scheduling decisions, putting the problem closer to the reality of companies that control dynamically the inventory of their customers. On the other hand, the problem becomes more challenging, requiring the use of sophisticated solution strategies, especially when considering practical constraints. The objective of this project is to propose formulations and solution methods for the IRP, to contribute to the state-of-the-art in solving the basic variant of the problem as well as to effectively solve formulations that incorporate practical features. We intend to propose heuristic and exact methods, to obtain good-quality solutions in reasonable time, lower and upper bounds and optimal solutions. The exact methods will be based on interior point branch-price-and-cut methods, which have the potential to result in effective methods, even for large-scale problems. In addition, we intend to propose a hybrid method that combines the main advantages of the other proposed methods. To validate and verify the proposed formulations and methods we will use instances from the literature and instances created from real-life data. (AU)
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