Abstract
This paper presents a hybrid discrete particle swarm optimization (HDPSO) for solving the traveling salesman problem (TSP). The HDPSO combines a new discrete particle swarm optimization (DPSO) with a local search. DPSO is an approach designed for the TSP based on the binary version of particle swarm optimization. Unlike in general versions of particle swarm optimization, DPSO redefines the particle’s position and velocity, and then updates its state by using a tour construction. The embedded local search is implemented to improve the solutions generated by DPSO. The experimental results on some instances are reported and indicate HDPSO can be used to solve TSPs.
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© 2006 Springer-Verlag Berlin Heidelberg
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Li, X., Tian, P., Hua, J., Zhong, N. (2006). A Hybrid Discrete Particle Swarm Optimization for the Traveling Salesman Problem. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_24
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DOI: https://doi.org/10.1007/11903697_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-47331-2
Online ISBN: 978-3-540-47332-9
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