DocumentCode
2071613
Title
An improved Time Adaptive Ant System
Author
Paul, A. ; Mukhopadhyay, Saibal
Author_Institution
Camellia Inst. of Technol., Electron. & Commun. Eng., Kolkata, India
fYear
2012
fDate
17-19 Dec. 2012
Firstpage
1
Lastpage
4
Abstract
Time Adaptive Ant System (TAAS) is the new proposed algorithm with modified pheromone updation rule. Here, we have exploited the properties of Time adaptive Least Mean Square (LMS) algorithm for the pheromone updation rule to resolve the basic shortcoming of easily falling into local optima and slow convergence speed. The improved algorithm has better global search ability and good convergence speed. A block diagram representation is also proposed, which may leads to stability analysis. Our algorithm is applied to Traveling Salesman Problem (TSP), and the simulation shows the effective results, as compared to other existing approaches.
Keywords
ant colony optimisation; convergence; evolutionary computation; least mean squares methods; search problems; travelling salesman problems; LMS algorithm; TAAS; TSP; adaptive least mean square algorithm; block diagram representation; convergence speed; global search ability; local optima; modified pheromone updation rule; stability analysis; time adaptive ant system; traveling salesman problem; Ant System; Time Adaptive Ant System; Time Adaptive LMS Algorithm; Travelling Salesman Problem;
fLanguage
English
Publisher
ieee
Conference_Titel
Computers and Devices for Communication (CODEC), 2012 5th International Conference on
Conference_Location
Kolkata
Print_ISBN
978-1-4673-2619-3
Type
conf
DOI
10.1109/CODEC.2012.6509352
Filename
6509352
Link To Document