International Journal of Computer Applications
Ant Colony Optimization (ACO) could be a comparatively new random heuristic approach for determination optimization issues. Furthermore, This paper extends these implementations with two local search methods and the authors compare two heuristics that guide the HACO algorithms. However, relatively few results on the runtime analysis of the ACO on the TSP are available. Moreover, they experiment with two different pheromone update strategies. In order to demonstrate this they present an ACO implementation for the travelling salesman problem it requires a larger number of ants and iterations which consume more time.