An improved ant colony algorithm was proposed with the unlimited step length of finding optimal path. It aims at the shortcomings of the traditional ant colony algorithms such as the single step length of finding the optimal path, tendency to fall into local optima and poor convergence. The diversity of choosing a path of ant was increased, further optimizing results, the heuristic information adopting a long step priority was improved at the same time, and a different update mode of local information through choose/pass grid was adopted. Simulation results showed that, the free step length ant colony algorithm could find a shorter path and its convergence was better compared with the traditional ant colony algorithms.
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