ROUTE OPTIMIZATION WITH ITERATED LOCAL SEARCH AND 3-OPT: A STUDY APPLIED TO URBAN DELIVERY LOGISTICS

This study presents the application of the Iterated Local Search (ILS) meta-heuristic, combined with the 3-Opt heuristic, for the optimization of delivery routes of a road transport company in Aracaju/SE. The research is applied, quantitative, exploratory and descriptive, based on the Traveling Salesman Problem (PCV). The data were obtained from real coordinates and processed by algorithms in Python. The proposed solution was compared with the company's current routing and with results from the literature, showing reductions of up to 38.36% in the distance traveled and savings of more than two hours in the daily commute time. The results demonstrate the feasibility of the model and its effectiveness in improving logistics indicators, such as cost reduction and increased operational efficiency, reinforcing the use of heuristics in decision support in urban logistics.