Sugarcane Harvesting Fronts Scheduling with multiple plants

• Grant number: 25/00494-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: August 01, 2025
• End date: February 28, 2027
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Reinaldo Morabito Neto
• Grantee: Pedro Peverari di Lallo
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated research grant: 22/05803-3 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings, AP.TEM

Abstract

The present research project focuses on optimizing the scheduling and routing of sugarcane harvesting operations in sugar-energy mills, with an emphasis on integrating tactical and operational decisions. It also considers scenarios where multiple industrial plants share the same agricultural blocks. The objective is to develop an optimization approach based on Mixed-Integer Programming (MIP) models to represent and address the problem, tackling issues such as the allocation of harvesting fronts, operation sequencing, and compatibility across different planning levels. Both exact and heuristic solution methods will be explored to derive effective solutions for real-world situations. The project is motivated by the lack of optimization approaches addressing this problem in the scientific literature and, as far as is known, also in several companies within this sector, which exhibits high logistical complexity and strategic importance for the state of São Paulo and Brazil. This research aims to contribute by proposing alternative integrated approaches for medium- and short-term planning in scenarios involving multiple industrial plants sharing agricultural blocks, rather than a single plant. The methodology includes mathematical modeling, the collection of operational data in collaboration with companies in the sector, computational implementation of the methods, and analysis and validation of results through computational experiments. The evaluation will be conducted using operational performance metrics and consistency across planning levels. It is expected that the project will contribute to improving the logistical practices of the sector by offering innovative solutions with practical application potential, both for academia and the industry. (AU)