Abstract

HERNANDEZ-OCANA, Betania; HERNANDEZ-TORRUCO, José; CHAVEZ-BOSQUEZ, Oscar  and  MONTANE-JIMENEZ, Luis G.. A Comparative Study of Bee and Ant Algorithms on the Sphere. Rev Politéc. (Quito) [online]. 2022, vol.50, n.2, pp.55-62. ISSN 2477-8990.

Abstract: Two bio-inspired algorithms in nature were implemented in order to know and analyze their behavior when looking for a solution to a numerical optimization problem well-known in the state of the art as a sphere problem. Likewise, we sought to detect common and particular aspects of both algorithms that lead to a premature convergence. These algorithms are: the Ant Colony Optimization Algorithm (ACO) and the Artificial Bee Colony (ABC). Both belong to the group of Collective Intelligence Algorithms, which simulate the collaborative behavior of certain simple and intelligent species. ACO and ABC are rarely used due to their low popularity in solving numerical optimization problems since they were originally developed for combinatorial problems. The results of five experiments are presented giving ACO as the best algorithm for the sphere problem.

Keywords : Optimization; Ant Colony; Artificial Bee Colony; Metaheuristics..

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