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 :
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