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Solving the Orienteering Problem Using Attractive and Repulsive Particle Swarm Optimization

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3 Author(s)
Herby Dallard ; Systems Science and Industrial Engineering Department, State University of New York at Binghamton Binghamton, NY 13902. Phone 607-777-4754 Fax 607-777-4094, ; Sarah S. Lam ; Sadan Kulturel-Konak

The initial study of this research applied the particle swarm optimization (PSO) heuristic to the orienteering problem (OP). PSO is a fairly new evolutionary heuristic-type algorithm created by Drs. Eberhart and Kennedy in 1995. Similar to ant colony optimization, motivation for PSO is nature-based on fish schooling and bees swarming. The OP is a variation of the well-known traveling salesmen problem (TSP) and is an NP-hard benchmark problem. Given a set of nodes with associated scores, the objective of the OP is to find a path that maximizes the total score subject to a given time (or distance) constraint. This paper presents an attractive and repulsive particle swarm optimization (ARPSO), which prevents PSO's weakness of premature convergence by maintaining solution diversity while retaining a rapid convergence. The ARPSO solves the OP with significant improvement in results when compared to PSO and is more competitive to known best published results.

Published in:

2007 IEEE International Conference on Information Reuse and Integration

Date of Conference:

13-15 Aug. 2007