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Grant number: 23/13720-3
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): December 01, 2023
Effective date (End): November 30, 2024
Field of knowledge:Engineering - Production Engineering - Operational Research
Principal Investigator:Diego Jacinto Fiorotto
Grantee:Ana Clara de Oliveira Lima
Host Institution: Faculdade de Ciências Aplicadas (FCA). Universidade Estadual de Campinas (UNICAMP). Limeira , SP, Brazil


In the context of Brazilian agribusiness, sugarcane production holds a prominent position, making Brazil one of the world leaders in this sector. The sugarcane production chain is constantly evolving and continuously seeking new technologies and tools that can enhance the planning and efficiency of the entire process. Within this chain, the sugarcane harvesting stage stands out as one of the most crucial and costly, and it is extremely important that this stage is carefully planned and executed in the most effective way possible. To support decision-making in this context, the identification of problems and the development of solutions through mathematical optimization models have proven valuable. The Rural Postman Problem (RPP) is a classic example of a challenge in the field of combinatorial optimization, often applied to solve complex logistical problems. Among arc-routing problems, the RPP aims to define the shortest and most efficient route to be taken by a postman (or vehicle), such that a subset of edges, referred to as required edges, are traversed. The RPP can be applied to various logistics problems, such as waste collection, mail and parcel delivery, and school and police transportation routes. In the context of sugarcane harvesting, the RPP emerges as an effective tool for representation and modeling, where the essential graph edges represent the sugarcane rows to be harvested, while the remaining edges symbolize the available spaces for the harvester's movement. This enables the use of optimization techniques to find the most efficient and cost-effective routes for sugarcane harvesting, contributing to more effective management of this critical process in the sugar-energy industry. Thus, this project proposes the application and study of the RPP in sugarcane harvesting through a review of problems already addressed in the literature, the development of mathematical models, computational studies, and the analysis of the obtained results.

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