A HYBRID APPROACH TO SOLVE THE TEAM ORIENTEERING PROBLEM

This paper addresses the resolution of the Team Orienteering Problem (TOP) through the integration of Iterated Local Search (ILS) and Fix-and-Optimize (F&O) metaheuristics. The TOP is a challenging combinatorial optimization problem classified as an NP-hard, whose objective is to maximize the total prize collected by a fleet of vehicles by determining the optimal sequence and selection of locations to visit for each vehicle, while adhering to the maximum route duration constraint. To evaluate the effectiveness of the proposed method, computational experiments were carried out using 82 instances from the existing literature, with the number of nodes ranging from 100 to 401. The algorithm was run 20 times for every instance and achieved 21 of the best known solutions, with an average relative deviation of 1.02% from the best known solutions. The results have shown that the proposed hybrid approach has a performance comparable to other algorithms documented in the literature.