A hybrid multi-objective evolutionary algorithm for the team orienteering problem

The Team Orienteering Problem (namely TOP) consists in finding the routings for a set of vehicles that maximize the total profit reached by visiting a series of customers. In this paper, a hybrid multi-objective evolutionary algorithm based on a special genetic algorithm and local search operators is proposed for approximately solving the TOP. Two conflicting objectives are considered: to minimize the total travel cost and to maximize the profit linked to the visited customers. The performance of the proposed method is evaluated on a set of benchmark instances extracted from Chao et al. [2] and its provided results are compared to those reached by the best methods available in the literature. Encouraging results have been obtained.