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考虑综合交通枢纽场站协调优化布局,在传统客运枢纽规划模型中增加用户对运输模式的选择与枢纽中转能力两个约束条件,提出基于容量限制与运输模式选择的综合客运多枢纽布局非线性整数规划模型,设计了改进的遗传算法对其进行求解。应用LINGO软件对布局优化模型进行有效性检验,对8节点Solomon标准测试数据进行计算,得出LINGO平均运算时间为5 102s,最优成本为1 899 782元;遗传算法MATLAB编程平均运算时间为59s,最优成本为1 948 796元。对50节点数据进行运算,平均运算时间为569s,最优成本为8 497 602元;使用25节点规模的AP数据集合,取枢纽数量为3时得出的最优成本为154 932元,应用传统枢纽规划模型进行求解,平均运算时间为607s,最优成本为155 098元,比经典算法降低了166元。可见,与传统枢纽规划模型相比,该模型与算法最优成本更少,说明改进的枢纽布局优化模型有效。
Considering the coordination and optimization layout of the integrated transportation hub station, adding the user’s choice of transportation mode and hub transit capacity in the planning model of the traditional passenger hub, this paper proposes two constraints of the integrated passenger transportation and multi-hub layout based on the capacity restriction and transport mode selection The model is designed and an improved genetic algorithm is designed to solve it. LINGO software was used to validate the layout optimization model, and the 8-node Solomon standard test data was calculated. The average operating time of LINGO was 5 102s and the optimal cost was 1 899 782. The average computing time of genetic programming with MATLAB was 59s , The optimal cost is 1,948,796 yuan. The average operation time is 569s and the optimal cost is 849760 yuan. Using the 25-node AP data set and taking the hub number as 3, the optimal cost is 154 932 yuan. The pivotal planning model solves the problem. The average computing time is 607s, the optimal cost is 155,098 yuan, which is 166 yuan lower than the classical algorithm. It can be seen that compared with the traditional hub planning model, the optimal cost of the model and the algorithm is less, which shows that the improved hub layout optimization model is effective.