DocumentCode
2952391
Title
An Exploration Technique for the Ant Colony System Optimization Framework
Author
Lv, Zhimeng ; Chen, Yong
Author_Institution
Comput. Sci. & Software Instn., Tianjin Polytech. Univ., Tianjin, China
fYear
2011
fDate
30-31 July 2011
Firstpage
1
Lastpage
4
Abstract
Traveling salesman problem (TSP) is a well known combinatorial optimization problems. Ant Colony Algorithm (AC) is new Heuristic Optimization Algorithm. It is widely used in TSP. Ant Colony System (ACS) is the improvement of AC, but it is still not enough being perfect, WMASC follows this approach and tries to improve the performance of ACS algorithm by improving multiple ants and the worst ant which are allowed to updated global pheromone, adjusting the value of the parameter. The tests show that WMACS is better than ACS.
Keywords
minimax techniques; travelling salesman problems; ACS; TSP; WMASC; ant colony system optimization; combinatorial optimization problem; exploration technique; global pheromone; heuristic optimization algorithm; max-min ant system; traveling salesman problem; Cities and towns; Convergence; Evolutionary computation; Heuristic algorithms; Optimization; Partitioning algorithms; Software algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems Engineering (CASE), 2011 International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4577-0859-6
Type
conf
DOI
10.1109/ICCASE.2011.5997576
Filename
5997576
Link To Document