Optimizing ACO Algorithm for the TSP Through Parameter Modification

Ant Colony Optimization (ACO) is an algorithm that is used to optimize the path or solve optimization problems in particular cases, including route problems or Travelling Salesman Problems (TSP). The implementation of the ACO algorithm was applied by using the biological behavior of ants in real life, which uses pheromone trails to communicate indirectly. In parameters of the ACO algorithm, some variables will be analyzed by using the behavior of ants in real life, such as the number of ants, epoch of ants, distances, and evaluation. In this journal paper, ACO will focus on two parameters, which are the evaporation rate and epoch of ants, to obtain the nearest and best path for TSP by modifying the parameters in each experiment.