Performance Evaluation of Ant Colony Algorithm with New Parameters

In recently, the study of intelligent algorithm attracts more attention especially for the ant colony algorithm, which adapts to the new circumstances swiftly, and is robust. This paper studies and analyses the function and influence on ant colony algorithm with traditional parameters α, β and new parameters such as number of ants and iteration times in theory and practice, taking TSP as an example. The results show that the algorithm has not worked out better answer in latter simulation phase, which makes a foundation to optimize the ant colony algorithm in future.