智能交通平台运输路径最优选择建模仿真分析
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摘要
为了提高智能交通运输平台的运行效率,提升用户对路径规划、选择结果的满意度,针对当前路径选择模型中存在的路径规划时间较长、路径选择结果的可接受性较差等弊端,提出基于主客观权重的智能交通平台运输路径最优选择模型。利用层次分析法、定性分析与定量分析对用户主观偏好信息的权重进行度量,采用信息熵权法对道路的各项客观属性权重进行计算。结合归一化方法计算路径选择的主、客观组合权重,综合考虑用户对于不同路径的差异化评价指标权重,得到用户决策矩阵。将决策矩阵与非线性函数相结合,构建路径规划、选择模型,根据各规划路径的综合决策值排序获取最优路径。实验表明,所构建模型的运行效率高于实验对比方法,路径选择结果优于其它方法。
In this article, a model to select the optimal route of intelligent transportation platform based on subjective weight and objective weight was presented. Firstly, the analytic hierarchy process(AHP), qualitative analysis and quantitative analysis were used to measure the weight of subjective preference information of user. Secondly, the information entropy weight method was used to calculate the weight of each objective attribute of road. Thirdly, the normalization method was used to calculate the combination weight of subjectivity and objectivity of path selection. In addition, the user decision matrix was obtained by comprehensively considering different evaluation weights for different paths. Moreover, the decision matrix was combined with the nonlinear function to build the path planning and the selection model. Finally, the optimal path was obtained based on the sorting of comprehensive decision value of each planning path. Simulations prove that the proposed model has higher efficiency and better path selection result than other methods.
In this article, a model to select the optimal route of intelligent transportation platform based on subjective weight and objective weight was presented. Firstly, the analytic hierarchy process(AHP), qualitative analysis and quantitative analysis were used to measure the weight of subjective preference information of user. Secondly, the information entropy weight method was used to calculate the weight of each objective attribute of road. Thirdly, the normalization method was used to calculate the combination weight of subjectivity and objectivity of path selection. In addition, the user decision matrix was obtained by comprehensively considering different evaluation weights for different paths. Moreover, the decision matrix was combined with the nonlinear function to build the path planning and the selection model. Finally, the optimal path was obtained based on the sorting of comprehensive decision value of each planning path. Simulations prove that the proposed model has higher efficiency and better path selection result than other methods.
引文
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[6] 刘诗序,等. 双参考点路径选择模型及其实证研究[J]. 交通运输系统工程与信息, 2017,17(6):107-113.
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[8] 孙军霞,伊亚平,陈京荣. 基于博弈论混合策略下的路径选择模型[J]. 数学的实践与认识, 2017,47(4):136-141.
[9] 李雪岩,等. 基于动态参照点的多主体有限理性路径选择模型[J]. 复杂系统与复杂性科学, 2016,13(2):27-35.
[10] 唐德权,黄金贵,史伟奇. 基于大数据平台的动态车辆路径调度算法[J]. 计算机工程, 2018,44(1):74-78.
[2] 姜海洋,等. 战时运输风险评估模型及其路径优化研究[J]. 计算机工程与应用, 2016,52(17):235-242.
[3] 卫小伟. 基于改进遗传算法的多目标城市交通路径选择系统建模与仿真[J]. 计算机与数字工程, 2016,44(1):10-15.
[4] 张京敏,牛群. 关于城市物流配送交通路径规划仿真研究[J]. 计算机仿真, 2017,34(6): 367-371.
[5] 刘二辉,姚锡凡. 基于改进遗传算法的自动导引小车路径规划及其实现平台[J]. 计算机集成制造系统, 2017,23(3):465-472.
[6] 刘诗序,等. 双参考点路径选择模型及其实证研究[J]. 交通运输系统工程与信息, 2017,17(6):107-113.
[7] 段明义,张文. 一种改进的交通网络路径选择算法[J]. 公路交通科技, 2016,33(11): 120-125.
[8] 孙军霞,伊亚平,陈京荣. 基于博弈论混合策略下的路径选择模型[J]. 数学的实践与认识, 2017,47(4):136-141.
[9] 李雪岩,等. 基于动态参照点的多主体有限理性路径选择模型[J]. 复杂系统与复杂性科学, 2016,13(2):27-35.
[10] 唐德权,黄金贵,史伟奇. 基于大数据平台的动态车辆路径调度算法[J]. 计算机工程, 2018,44(1):74-78.