A matheuristic approach to the orienteering problem with service time dependent profits

Abstract This paper addresses the orienteering problem with service time dependent profits (OPSTP), in which the profit collected at each vertex is characterized by a nonlinear function of service time, and the objective is to maximize the total profits by determining a subset of the vertices to be visited and assigning appropriate service time to each of them within a given time budget. To solve this problem, a mixed integer nonlinear programming model is formulated, and a two-phase matheuristic algorithm that consists of a tabu search method and a nonlinear programming is implemented. Extensive computational experiments are conducted on both randomly generated instances and instances that are adapted from the TSPLIB. The results show that our proposed matheuristic algorithm could be quite effective in finding good-quality solutions.

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