Parameters Analysis Based on Experiments of Particle Swarm Optimization Algorithm for Solving Traveling Salesman Problem

Author

Zhang, Jiang-wei ; Zhang, De-xi

Author_Institution

Sch. of Comput. Sci. & Technol., Xuchang Univ., Xuchang, China

Volume

3

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

279

Lastpage

283

Abstract

An improved particle swarm optimization (IPSO) algorithm is proposed for solving traveling salesman problem (TSP) which is a well-known NP-complete problem. Based on the different experimental results, this paper analysis the parameters influences to the algorithm optimization ability. The IPSO algorithm can get a better global optimum in multiple TSP problems by setting the proper parameters. Numerical simulation results for the different scale benchmark TSP problems show the effectiveness and efficiency of the proposed method using the proper parameters.

Keywords

computational complexity; numerical analysis; particle swarm optimisation; travelling salesman problems; NP-complete problem; algorithm optimization ability; improved particle swarm optimization algorithm; parameters analysis; traveling salesman problem; Algorithm design and analysis; Benchmark testing; Computer science; Large-scale systems; NP-complete problem; Numerical simulation; Particle swarm optimization; Simulated annealing; Space exploration; Traveling salesman problems; Parameters Analysis; Particle Swarm Optimization algorithm; Traveling Salesman Problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.601

Filename

5365144