DocumentCode
2341914
Title
A hybrid ant colony algorithm for global optimization of continuous multi-extreme functions
Author
Ge, Yan ; Meng, Qing-Chun ; Yan, Wan-Jun ; Xu, Jing
Author_Institution
Dept. of Comput. Sci., Ocean Univ. of China, Qingdao, China
Volume
4
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
2427
Abstract
A hybrid optimization technique is proposed for global optimization of continuous multi-extreme functions. The scheme incorporates a deterministic searching algorithm (the Powell method) into the ant colony algorithm. This hybrid method can improve the optimization performance and enhance the fast convergence during the local search of the ant colony algorithm. Experimental results of the global optimization of two continuous multi-extreme functions indicate the effectiveness and the applicability of the proposed algorithm.
Keywords
convergence; deterministic algorithms; optimisation; search problems; continuous multiextreme function; deterministic search algorithm; global optimization; hybrid ant colony algorithm; Algorithm design and analysis; Ant colony optimization; Computer science; Convergence; Hybrid intelligent systems; Legged locomotion; Marine technology; Oceans; Space exploration; Traveling salesman problems;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382210
Filename
1382210
Link To Document