We use ant colony optimization (ACO) algorithm for solving combinatorial optimization problems such as the traveling salesman problem. Some applications of ACO are: vehicle routing, sequential ordering, graph coloring, routing in communications networks, etc. In this paper, we compare the performance of ACO to that of a few other state-of-the-art algorithms currently in use and thus measure the effectiveness of ACO as one of the major optimization algorithms in regard with a few more algorithms. The performance of the algorithms is measured by observing their capacity to solve a traveling salesman problem (TSP). This paper will help to find the proper algorithm to be used for routing problems in different real-life situations.

How to Cite
SAIFUL ISLAM, MASHRURE TANZIM, SADIA AFREEN, GERALD ROZARIO, A.H.M. Evaluation of Ant Colony Optimization Algorithm Compared to Genetic Algorithm, Dynamic Programming and Branch and Bound Algorithm Regarding Travelling Salesman Problem. Global Journal of Computer Science and Technology, [S.l.], july 2019. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/1855>. Date accessed: 30 mar. 2020.