New ideas for applying ant colony optimization to the probabilistic TSP

Authors:
Jürgen Branke;Michael Guntsch
Affiliations:
Institute AIFB, University of Karlsruhe, Germany;Institute AIFB, University of Karlsruhe, Germany
Venue:
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Year:
2003

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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.