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为了诱导车辆在出行时选择较高质量的路线,提出并建立了城市道路权值仿真模型.为求解该模型,从分析基本蚁群算法入手,通过在状态转移规则中加入扰动因子,改进全局更新规则,以及引入信息素更新算子改进了蚁群算法.然后利用道路权值模型对两种算法在路径寻优效果上做了比较和分析,实验结果表明改进后的蚁群算法能有效地避免停留在局部最优解,并提高计算效率,具有良好的寻优性和收敛性,能准确找出路网中满足综合要求的最优路径.
In order to induce the vehicle to choose a higher quality route while traveling, a simulation model of urban road weight is proposed and established.In order to solve this model, starting with the analysis of basic ant colony algorithm, by adding disturbance factor into the state transition rule, Rules, and the introduction of pheromone update operator to improve the ant colony algorithm.And then use the road weight model to compare and analyze the two algorithms in the path optimization, the experimental results show that the improved ant colony algorithm can effectively avoid Stay in the local optimal solution and improve the computational efficiency, with good search and convergence, can accurately find the optimal route to meet the comprehensive requirements in the road network.