Optimization of Waste Collection Routes in the Historic Center of Cuernavaca Using a Simulated Annealing Metaheuristic Approach

Abstract Solid waste management is a global challenge affecting governments and the population. It is estimated that more than two billion metric tons of municipal solid waste are generated each year, and this number is expected to increase to 3.4 billion metric tons by 2050. In this context, this article presents a Simulated Annealing metaheuristic approach for solving the municipal solid waste management problem by optimizing the collection routes of waste trucks to minimize total travel distance while remaining within vehicle capacity limits based on the capacitated vehicle routing problem. The exploration operator of the proposed approach applies two neighborhood procedures to analyze different collection routes with varying vehicle capacities. Four realistic problem instances are analyzed, considering the distances for waste truck scheduling and the volumes of waste disposed in the historic center of Cuernavaca, Mexico. The proposed approach was efficient in computing municipal solid waste collection routes and improved from 2.2 to 15.1% on the studied problem instances over a reference solution computed by an exact resolution method. The results demonstrate that the proposed approach enhances the efficiency of municipal waste collection routes, contributing to a cost-effective waste management system.