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A Modified Ant System using Gaussian Probabilistic Pheromone Updation Technique

Anirban Pal*, Debarghya Das**, Abhishek Paul***

*-**-*** Department of Electronics and Communication, Camellia Institute of Technology. Kolkata, India.

Periodicity:April - June'2012
DOI : https://doi.org/10.26634/jse.6.4.1804

Abstract

Ant Colony Optimization (ACO) is mainly inspired by the foraging behavior of ants. In this paper, we have proposed a modified model for ant system, entitled as Gaussian Probabilistic Ant System (GPAS) for probabilistic pheromone updating. This proposed algorithm is implemented by incorporating a probabilistic property in the pheromone trail deposition factor, stated as ? (rho).We use the equation proposed by Karl Friedrich Gauss, well-known mathematician and physical scientist, in our GPAS, for updating ?. Trail deposition factor, ?, is in general a static factor and here it has been made probabilistic so as to increase the effectiveness of the ant system in finding the optimal tour for Traveling Salesman Problem (TSP). GPAS modifies its properties in accordance to the requirement of surrounding domain and for the betterment of its performance in dynamic environment. The experimental evaluation conducted to find out the usefulness of the new strategy, using selective benchmark problems from TSP library [6]. Our algorithm shows effective and comparable results as compared to other existing approaches.

Keywords

Ant System (AS), Ant Colony Optimization (ACO), Gaussian Probabilistic Ant system (GPAS), Traveling Salesman Problem (TSP).

How to Cite this Article?

Pal A, Das D and Paul A. (2012). A Modified Ant System using Gaussian Probabilistic Pheromone Updation Technique. i-manager’s Journal on Software Engineering, 6(4), 16-22. https://doi.org/10.26634/jse.6.4.1804

References

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[9]. A. Paul and S. Mukhopadhyay, A. Paul and S.Mukhopadhyay, “An Adaptive Pheromone Updation of the Ant System using LMS Technique”, in Proc. Int. Conf. on Modelling, Optimization and Computing (ICMOC-2010), AIP, 2010, vol. 1298, pp. 498-503.

[10]. L.M. Gambardella, E.D. Taillard, and G. Agazzi, “MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows,” in New Ideas in Optimization, D.Corne et.al.,Eds. McGraw Hill, London, UK, 1999, pp.63.76.

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A Modified Ant System using Gaussian Probabilistic Pheromone Updation Technique

Abstract

Keywords

How to Cite this Article?

References

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