ABSTRACT
There are different algorithms based on the simulation of natural processes and genetics such as genetic algorithm s and Ant Colony Optimization
(ACO), based on heuristic problem solving (Bianchi et al. 2002). Nowadays, ACO is used to solve more complex problems, which require a lot of processing time for achieving results (Barán and Sosa 2000). Therefore, we can work with highly complex problems getting results with less processing time with a parallel implementation. In this paper, we describe several variants of Ant Colony Optimization (ACO) to solve the Traveling Salesman Problem (TSP) allowing the user to input parameters using a graphical interface and performing parallel processing.
