| With the rapid development of motorization, traffic problems in city have become in-creasingly prominent, which has affected the socio-economic development seriously. Devel-oping urban public transport vigorously and optimizing public transportation network be-comes one of the main effective ways of solving this problem. Transportation network, as the base of public transport system, plays a significant role in the development of this system. Optimizing public transportation network not only fulfill the potential of public transport sys-tem, improve the utilization of transportation resources, but is an effective and feasible meas-ure. Ant colony algorithm is a new heuristic algorithm, which has better performance for solving various combinatorial optimization problems, so this article will apply ant colony op-timization algorithm to solve the public transportation network optimization.Firstly, the paper introduces public transportation network optimization methods, through summing up the public transportation network optimization factors, leads to the goal of the network optimization. According to the transportation network optimization constraints, combined with the "one by one routed, then optimizing into the network", the paper proposes the optimization model based on the largest passenger flow. Secondly, it points out the ant colony algorithm systematically, specifically describes the basic principles and models of ant colony algorithm, and the application of TSP, and then, analyses the various parameters of the algorithm by experiments, gives the range of algorithm parameters. On this basis, the paper presents the improved ant colony algorithm which is applicable to the public transport network. Finally, Yangjiang in Guangdong Province is provided as an example, on the basis of the improved ant colony algorithm, it makes optimization of Yangjiang City public transportation network, and evaluates the results of the optimization. |
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