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An Ant-Based Heuristic for the Railway Traveling Salesman Problem

  • Petrica C. Pop
  • Camelia M. Pintea
  • Corina Pop Sitar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4448)

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.

Keywords

Synthetic Data Travel Salesman Problem Tabu List Good Tour Elementary Connection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Petrica C. Pop
    • 1
  • Camelia M. Pintea
    • 2
  • Corina Pop Sitar
    • 3
  1. 1.Department of Mathematics and Computer Science, Faculty of Sciences, North University of Baia MareRomania
  2. 2.Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-NapocaRomania
  3. 3.Faculty of Economics, Babes-Bolyai University of Cluj-NapocaRomania

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