Abstract
The shortest path problem is one of the most critical issues of intelligent transportation systems. Ant colony algorithm is an effective intelligent optimization method to solve the shortest path problem. However, there are some drawbacks when basic ant colony algorithm is used in solving the shortest path problem. So in this paper the basic ant colony algorithm is improved, so that the improved ant colony algorithm is suitable for solving the shortest path problem. In order to improve the efficiency of the algorithm, the search scope is limited, and the transfer rule and the ant colony algorithm pheromone update rule are improved. Simulation results show that the improved ant colony algorithm can efficiently obtain the shortest path.
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