Chaotic Immune PSO Algorithm for Traveling Salesman Problem
In connection with the drawback that the Particle Swarm Optimization algorithm is easy to fall in local extremum in solving the TSP, based on the learning of the existing results, and take advantage of the ergodicity and the intrinsic randomness of chaos, and inspired by the immune mechanism of organism immune system, and introduce the chaos optimization method and the information processing mechanisms of the immune system to PSO, we proposed a chaotic immune particle swarm optimization algorithm, and make use of the algorithm to solving the TSP. Experimental results show that the algorithm can distinguished improve the convergence performance of PSO algorithm, and the efficiency of searching has been improved significantly.
KeywordsPSO algorithm Chaos Artificial Immune TSP
Unable to display preview. Download preview PDF.
- 1.Yang, W.-B., Zhao, Y.-W.: Improved simulated annealing algorithm for TSP. Computer Engineering and Applications 46 (15), 34–36 (2010)Google Scholar
- 5.Yuan, Z., Yang, L., Wu, Y.: Chaitic patticle sarm optimization algorithm for traveling salesman problem. In: Proceedings of the IEEE International Conference on Automation and Logistics, vol. 1, pp. 121–124 (2007)Google Scholar
- 8.Jiao, L.C., Du, H.F.: Development and Prospect of the Artificial Immune System. Acta Electronica Sinica 31(9), 73–80 (2003)Google Scholar
- 9.Xie, K.G., Zeng, X.H.: Comparative Analysis between Immune Algorithm and Other Random Searching Algorithms. Journal of Chongqing University 26(11), 14–17 (2003)Google Scholar
- 10.Clerc, M.: Discrete Particle Swarm Optimization Illustrated by the Traveling Salesman Problem, http://www.mauriceclerc.net
- 11.Chen, C., Xu, C., Bie, R., Gao, X.Z.: Artificial Immune Recognition. System for DNA Microarray Data Analysis. In: Fourth Intenational Conference on Natural Computation ICNC 2008, vol. 6, pp. 633–637 (2008)Google Scholar
- 12.Chang, Z., Zhu, G.: Application on Express Delivery of an Immune Genetic Algorithm Based on Machine Learning. In: Second International Symposium on Computational Intelligence and Design ISCID 2009, vol. 2, pp. 165–167 (2009)Google Scholar