Abstract
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 RTSP is 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. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Pop, P. C., Pintea, C. M., & Sitar, C. P. (2007). An ant-based heuristic for the railway traveling salesman problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4448 LNCS, pp. 702–711). Springer Verlag. https://doi.org/10.1007/978-3-540-71805-5_76
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