An Ant-Based Heuristic for the Railway Traveling Salesman Problem

We consider the Railway Traveling Salesman Problem, denoted RTSP, in which a salesman using the railway network wishes to visit a certain number of cities to carry out his/her business, starting and ending at the same city, and having the goal to minimize the overall time of the journey. The RTSPis NP-hard and it is related to the Generalized Traveling Salesman Problem. In this paper we present an effective meta-heuristic based on ant colony optimization (ACO) for solving the RTSP. Computational results are reported for real-world and synthetic data. The results obtained demonstrate the superiority of the proposed algorithm in comparison with the existing method.