A hybrid discrete particle swarm optimization for the traveling salesman problem

Authors:
Xiangyong Li;Peng Tian;Jing Hua;Ning Zhong
Affiliations:
College of Economics & Management, Shanghai Jiaotong University, Shanghai, P.R. China;College of Economics & Management, Shanghai Jiaotong University, Shanghai, P.R. China;College of Economics & Management, Shanghai Jiaotong University, Shanghai, P.R. China;College of Economics & Management, Shanghai Jiaotong University, Shanghai, P.R. China
Venue:
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Year:
2006

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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.