容量限制与运输模式联合选择的综合客运枢纽布局模型(英文)

Comprehensive passenger hub layout model of combined selection for capacity limitation and transportation mode

分析了传统的综合客运枢纽布局优化模型,同时增加运输模式与中转能力的约束条件,提出了改进后的综合客运枢纽布局优化模型,并设计了改进的遗传算法对其求解。应用LINGO软件进行有效性检验,分别计算了8节点与50节点Solomon标准测试数据,并将改进模型与经典算法进行比较。计算结果表明:当应用LINGO软件计算8节点Solomon标准测试数据时,平均运算时间为5 043s,最优成本为1 952 418元,应用遗传算法与MATLAB软件计算的平均运算时间为62s,最优成本为1 955 900元;当应用遗传算法与MATLAB软件计算50节点Solomon标准测试数据时,平均运算时间为574s,最优成本为8 500 600元;当计算25节点的AP数据且枢纽节点数量为3时,平均运算时间为612s,最优成本为155 148元,比经典算法降低了108元。可见,改进模型有效。

The traditional optimization model of comprehensive passenger hub layout was analyzed, and the constraints of transportation mode and transfer capability were considered simultaneously. The improved optimization model of comprehensive passenger hub layout was proposed, and the improved genetic algorithm was introduced to solve the model. LINGO software was used to test the effectiveness, Solomon standard test data with 8 and 50 nodes were calculated respectively, and the improved model was compared with the classical algorithm. Calculation result shows that while calculating Solomon standard test data with 8 nodes, the average running time is 5 043 s and the optimal cost is 1 952 418 yuan by using LINGO software, the average running time is 62 s and the optimal cost is 1 955 900 yuan by using genetic algorithm and MATLAB software. While calculating Solomon standard test data with 50 nodes, the average running time is 574 s and the optimal cost is 8 500 600 yuan by using genetic algorithm and MATLAB software. While calculating AP data set with 25 nodes and hub node number is 3, the average running time is 612 s and the optimal cost is 155 148 yuan, the optimal cost decreases 108 yuancompared with the classical algorithm. So the improved model is effective. 6 tabs, 6 figs, 20 refs.