Computer Science – Artificial Intelligence
Scientific paper
2008-11-02
Computer Science
Artificial Intelligence
16th IEEE International Conference on Advanced Computing and Communication, 2008
Scientific paper
The paper presents an exponential pheromone deposition approach to improve the performance of classical Ant System algorithm which employs uniform deposition rule. A simplified analysis using differential equations is carried out to study the stability of basic ant system dynamics with both exponential and constant deposition rules. A roadmap of connected cities, where the shortest path between two specified cities are to be found out, is taken as a platform to compare Max-Min Ant System model (an improved and popular model of Ant System algorithm) with exponential and constant deposition rules. Extensive simulations are performed to find the best parameter settings for non-uniform deposition approach and experiments with these parameter settings revealed that the above approach outstripped the traditional one by a large extent in terms of both solution quality and convergence time.
Acharya Ayan
Banerjee Aritra
Janarthanan Ramadoss
Konar Amit
Maiti Deepyaman
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