Solving Path Planning Problem by an ACO-PSO Hybrid Algorithm
Authors
Chun-xue Shi1, Bu Ying-yong, Li Zi-guang, Tan Jun
1School of Mechanical and Electronical Engineering, Center South University
Corresponding Author
Chun-xue Shi
Available Online October 2007.
- DOI
- 10.2991/iske.2007.91How to use a DOI?
- Keywords
- ant colony optimization (ACO); particle swarm optimization (PSO); hybrid algorithm; robot path planning problem
- Abstract
An ACO-PSO Hybrid Algorithm Solving Path Planning Problem based on Swarm Intelligence(SI) is proposed. The problem first is described and some corresponding definitions are presented. Ant colony optimization (ACO) is used to establish the corresponding solution, and some material algorithm steps are set out. Particle swarm optimization (PSO) is applied to optimize the parameters in ACO, and parameters can be selected self- adaptively. Through the steps above, algorithm performance can be greatly enhanced and the reliability of parameters selecting can be guaranteed. At last simulation experiments are carried out, and the results prove the veracity of the algorithm.
- Copyright
- © 2007, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Chun-xue Shi AU - Bu Ying-yong AU - Li Zi-guang AU - Tan Jun PY - 2007/10 DA - 2007/10 TI - Solving Path Planning Problem by an ACO-PSO Hybrid Algorithm BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 536 EP - 539 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.91 DO - 10.2991/iske.2007.91 ID - Shi2007/10 ER -