A New Pheromone Control Algorithm of Ant Colony Optimization

The Ant Colony Optimization (ACO) is one of the most powerful optimization methods. Many works have done for combinational optimization problems using ACO. The main search mechanism of ACO is pheromone communication of each ant. Most of these previous works adopt the same pheromone control algorithm. In this paper, we proposed a new pheromone control algorithm to improve the search performance and to reduce the processing steps. No previous studies have, to our knowledge, applied the additional pheromone control. Experimental result to evaluate the proposed algorithm shows improvement comparison with normal pheromone control algorithm.