Routing and Scheduling of Sugarcane Harvest Fronts: Models and Heuristic Methods

• Grant number: 24/14421-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2024
• End date: September 30, 2025
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Pedro Augusto Munari Junior
• Grantee: João Vitor Tribst Guion
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

Since colonial times, sugarcane has been widely exploited as a raw material for sugar production. Currently, its growing exploitation is related to the increased use of bioenergy, bioplastics, and especially biofuels. Due to this expanding demand, there is a need to improve the agricultural stage of this raw material, where the highest production costs occur. This stage involves planting and the operations of harvesting, transshipment, and transportation (HTT). In particular, HTT operations are carried out by harvest fronts, which involve the allocation and routing of vehicles, consisting of harvesters as well as transshipment and transport trucks, whose use must be as efficient as possible. Thus, the aim of this project is to understand, implement, and develop mathematical models and heuristic methods that assist in decision-making involving the routing and scheduling of sugarcane harvest fronts, with a focus on the harvesting and transshipment stages. The intention is to extend models and algorithms recently proposed in the literature on the vehicle routing problem (VRP), especially considering variants with split deliveries, to address the specificities of the studied situation. The project will be based on real data and requirements provided by a company operating in the field. Thus, proposed and existing approaches will be compared by conducting computational experiments with data from literature instances, as well as those obtained in practice. Therefore, the project has the potential to result in theoretical contributions through the proposal of new models and solution methods, as well as practical contributions by offering ways to improve decision-support tools.