Solution optimization of ACO in TSP by modification of parameters

Ant Colony Optimization is an optimization algorithm used to solve complex optimization problems. The ACO algorithm implementation was inspired by the biological behavior of ants, which involves a large population with indirect communication via pheromone trails. There are a few solutions discussed in the literature on implementing the ACO algorithm in real life. Based on the behavior of real ants, the Ant Colony Optimization algorithm has shown good results in several well-known complex problems, such as the travelling salesman problem. One of the main objectives of the TSP is to find the optimal route to visit all the cities or locations with the condition of travelling to each city only once. In this journal paper, a few ACO implementations in real life are analyzed and how to obtain the best path by tuning the parameters.