DocumentCode
2254658
Title
An improved ant colony algorithm for continuous space optimization
Author
Yang, Liang ; Fu, Zheng-qi ; De Wang ; Li, He-long ; Xia, Jing-bo
Author_Institution
Coll. of Sci., Huazhong Agric. Univ., Wuhan, China
Volume
4
fYear
2010
fDate
11-14 July 2010
Firstpage
1829
Lastpage
1832
Abstract
Based on the mechanism of the improved ant colony algorithm, a novel method in continuous space optimization is developed. Four novel strategies are used in this new method: add random ants and elitist ants, improve the move strategy, alter the parameters dynamically, and modify the peak value in the pheromone distribution function. Simulation results show that the improved algorithm achieves faster convergence speed and better global optimization, while compared with the simulation results of original algorithm.
Keywords
convergence; optimisation; ant colony algorithm; continuous space optimization; convergence speed; elitist ants; global optimization; random ants; Algorithm design and analysis; Convergence; Distribution functions; Heuristic algorithms; Machine learning algorithms; Optimization; Simulation; Ant colony algorithm; Continuous function optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-6526-2
Type
conf
DOI
10.1109/ICMLC.2010.5580957
Filename
5580957
Link To Document