An Ant-Based Heuristic for the Railway Traveling Salesman Problem

Authors:
Petrica C. Pop;Camelia M. Pintea;Corina Pop Sitar
Affiliations:
Department of Mathematics and Computer Science, Faculty of Sciences, North University of Baia Mare, Romania;Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-Napoca, Romania;Faculty of Economics, Babes-Bolyai University of Cluj-Napoca, Romania
Venue:
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Year:
2009

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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 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.