Otimização da rede logística reversa de embalagens de defensivos agrícolas usando localização de facilidades e roteirização de veículos no estado do Tocantins

Abstract

The reverse logistics of empty pesticide packaging represents a significant challenge in regions with strong agricultural activity, especially in states with large territorial dispersion and infrastructure constraints, such as Tocantins. Despite regulatory advances promoted by the National Solid Waste Policy, the literature still lacks integrated models capable of simultaneously addressing the definition of collection facility locations and the operational planning of pickup routes while considering the seasonal nature of waste generation. In this context, this research aims to develop a decision-support model able to determine the optimal configuration of the logistics network and the associated transportation routes. To estimate demand, official data on cultivated areas of major crops were combined with average packaging generation coefficients per hectare, allowing the calculation of monthly volumes for each municipality. The methodological approach integrates the Facility Location Problem and the Capacitated Vehicle Routing Problem, solved through metaheuristics, with emphasis on Genetic Algorithms and Ant Colony Optimization. The model incorporates fixed implementation costs for facilities and variable transportation costs, enabling the evaluation of the economic balance of the operation. The results indicated that the installation of six collection centers provides the best configuration for the state, ensuring efficient territorial coverage and a significant reduction in traveled distances. In the routing stage, the obtained solutions showed high average vehicle utilization rates, computational stability, and strong adherence to the spatial distribution of agricultural production, with variations associated with seasonal demand patterns throughout the analyzed months. It is concluded that the integrated application of optimization techniques and metaheuristics provides robust support for reverse logistics planning, contributing to greater operational efficiency, cost reduction, and reinforcement of environmental compliance.