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中文摘要：
在轴辐式网络中枢纽间干线运输成本相对于运量而言具有非线性的规模经济效应,在轴辐式网络单分配模型的基础上,改变传统研究中将规模经济效应处理为折扣系数常量的方法,建立基于可变规模经济效应的非线性模型,应用遗传算法进行求解。通过算例,对基本模型和考虑规模经济效应的非线性模型进行求解,得出枢纽点的选择及非枢纽点的分配方案,进而对两方案进行比较。研究结果得出：非线性规模经济效应对枢纽点选择和分配会产生影响,并能减少成本。此外,遗传算法是基于群体的一种仿生算法,能有效解决大规模的轴辐式网络枢纽选址问题。
英文摘要：
In a hub-and-spoke network, the transportation cost of hub-hub truck lines is nonlinearly affected by the economies of scale with respect to transported volume. Based on a single allocation model of hub-and-spoke network, to change the traditional method whose effects of economies of scale is treated by constant discount factors, a nonlinear programming model is devised to present the nonlinear effects of economies of scale by the transported volume, which is solved by taking genetic algorithm. In these examples, the basic model and the non-linear model considering variable effects of economies of scale are solved respectively, which concludes the hub selection and non-hub allocation scheme. Then, the comparison is made between the two schemes. The results show that nonlinear effects of economies of scale have influence on hub selection and allocation and can reduce the transportation costs. Besides, as a bionic algorithm based on groups, genetic algorithm can solve large-scale hub location problem of hub-and-spoke network effectively.
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