CFP last date
22 April 2024
Reseach Article

Solving City Routing Issue with Particle Swarm Optimization

by Sarman K. Hadia, Arjun H. Joshi, Chaitalee K. Patel, Yogesh P Kosta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 15
Year of Publication: 2012
Authors: Sarman K. Hadia, Arjun H. Joshi, Chaitalee K. Patel, Yogesh P Kosta
10.5120/7266-0348

Sarman K. Hadia, Arjun H. Joshi, Chaitalee K. Patel, Yogesh P Kosta . Solving City Routing Issue with Particle Swarm Optimization. International Journal of Computer Applications. 47, 15 ( June 2012), 30-38. DOI=10.5120/7266-0348

@article{ 10.5120/7266-0348,
author = { Sarman K. Hadia, Arjun H. Joshi, Chaitalee K. Patel, Yogesh P Kosta },
title = { Solving City Routing Issue with Particle Swarm Optimization },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 15 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 30-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume47/number15/7266-0348/ },
doi = { 10.5120/7266-0348 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:42:28.474577+05:30
%A Sarman K. Hadia
%A Arjun H. Joshi
%A Chaitalee K. Patel
%A Yogesh P Kosta
%T Solving City Routing Issue with Particle Swarm Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 15
%P 30-38
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The city routing issue is the problem to find a shortest tour of minimum length on a fully connected graph. Various Nature-inspired algorithms have been proposed towards this problem. This paper proposes an application of Particle Swarm Optimization for this Issue. Results are achieved with the concept of Swap Operator and Sequence of Swap.

References
  1. Angeline P. Evolutionary Optimization versus Particle Swarm Optimization: Philosophy and Performance Difference. The 7th Annual Conference. On Evolutionary Programming, San Diego, USA, 1998.
  2. Huang Lan Zhou Chunguang,Wang Kangping. Hybrid Ant . Colony algorithm for Traveling Salesman Problem. Progress In' Natural Science. Vol 13 No. 4(Cbina),April2003.
  3. Kang-Ping Wang, lan Huang, Chun-Guang Zhou, Wei Pang, " Particle Swarm Optimization For Travelling Salesman Problem", IEEE 2003.
  4. Kennedy J, and Spears W. Matching algorithms to Problems: An Experimental Test of the Particle Swarm and Some Genetic Algorithms on the Multimodal Problem Generator. IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, 1998.
  5. Kennedy J, Eberhart R. Particle Swarm Optimization, IEEE International Conference on Neural Networks (Perth, Australia), IEEE Service Center, Piscataway, NJ, IV: 1942-1948, 1995.
  6. KP. Wang, L. Huang, C. G. Zhou, W. Pang, Particle swarm optimization for traveling salesman problem, International conference on Machne Learning and Cybernatics 3 (2003) 1583-1585
  7. M. Clerc, in: Discrete Particle Swarm Optimization, illustrated by the Traveling Salesman Problem New Optimization Techniques in Engineering, Springer, 2004, pp. 219–239.
  8. M. Clerc, Discrete particle swarm optimization illustrated by the traveling salesman problem, http://www. mauriceclerc. net, 2000.
  9. Shuang Cong, Yajun Jia and Ke Deng, " Particle Swarm And Ant Colony Algorithms and their Applications in Chinese Traveling Salesman Problem"
  10. Zhou C G et al. Computing Intelligence (in Chinese) Changchnn: Publishing House of Jilin University, 1585.
Index Terms

Computer Science
Information Sciences

Keywords

Flocking Basic Swap Sequence (bss) Vehicular Ad-hoc Network (vanet)