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New Ideas for Applying Ant Colony Optimization to the Probabilistic TSP

  • Jürgen Branke
  • Michael Guntsch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2611)

Abstract

The Probabilistic Traveling Salesperson Problem (PTSP) is a stochastic variant of the Traveling Salesperson Problem (TSP); each customer has to be serviced only with a given probability. The goal is to find an a priori tour with shortest expected tour-length, with the customers being served in the specified order and customers not requiring service being skipped. In this paper, we use the Ant Colony Optimization (ACO) metaheuristic to construct solutions for PTSP. We propose two new heuristic guidance schemes for this problem, and examine the idea of using approximations to calculate the expected tour length. This allows to find better solutions or use less time than the standard ACO approach.

Keywords

Solution Quality Full Evaluation Approximation Depth Heuristic Information Evaluation Depth 
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 2003

Authors and Affiliations

  • Jürgen Branke
    • 1
  • Michael Guntsch
    • 1
  1. 1.Institute AIFBUniversity of Karlsruhe (TH)Germany

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