Improving Ant Colony Algorithm with Parameters Variation Mechanism

The routes searching strategy and the parameters control strategy of ant colony optimization algorithm (ACO) is studied and the limitations of these strategies are analyzed. To increase the performance of ACO, the improved ant colony system based on parameters variation mechanism (VPACS) is proposed. Some examples of traveling salesman problems are given, which are simulated by using AS, ACS, MMAS and VPACS. The simulation results show that VPACS has excellent global optimization properties and much fast convergence speed, and it can avoid premature convergence and stagnancy of ACO.