Ant Colony Optimization (ACO) and a Variation of Bee Colony Optimization (BCO) in Solving TSP Problem: A Comparative Study

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 9
Year of Publication: 2014
Muhammed Basheer Jasser
Mohamad Sarmini
Rauf Yaseen

Muhammed Basheer Jasser, Mohamad Sarmini and Rauf Yaseen. Article: Ant Colony Optimization (ACO) and a Variation of Bee Colony Optimization (BCO) in Solving TSP Problem: A Comparative Study. International Journal of Computer Applications 96(9):1-8, June 2014. Full text available. BibTeX

	author = {Muhammed Basheer Jasser and Mohamad Sarmini and Rauf Yaseen},
	title = {Article: Ant Colony Optimization (ACO) and a Variation of Bee Colony Optimization (BCO) in Solving TSP Problem: A Comparative Study},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {9},
	pages = {1-8},
	month = {June},
	note = {Full text available}


Traveler sales man problem is known research problem which has a lot of industrial applications. A lot of algorithms has been proposed to solve TSP, some of Ant Colony Optimization (ACO) and Bee Colony Optimization (BCO) algorithms. BCO algorithm has variations and enhancements to improve the performance. In this paper, a experimental comparison study between the basic Ant Colony Optimization and enhanced Bee Colony Optimization algorithms is done. Both ACO and enhanced BCO have been implemented using MATLAB. The comparison study includes comparing the time consumed, solution quality and algorithmic complexity in order to prove the effictivness and efficiency of each. The experimental study showed that the basic ACO outperforms the enhanced BCO in the required consumed time to get the solution path, while enhanced BCO proved to provide better solution quality.


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