| 基于正交试验的乘用车运输网络优化方法 |
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| 引用本文： | 秦璐,刘弘超,孙智源.基于正交试验的乘用车运输网络优化方法[J].运筹与管理,2018,27(12):38-46. |
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| 作者姓名： | 秦璐 刘弘超 孙智源 |
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| 作者单位： | 1.北京交通大学 交通运输学院,北京 100044;2.中物协北京物流工程设计院,北京 100834;3.北京工业大学 城市交通学院,北京 100124 |
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| 基金项目： | 国家科技支撑计划(2014BAH24F01);中国博士后科学基金资助项目(2016M600887);北京市博士后工作经费资助项目(2017-ZZ-052);北京工业大学人文社科基金项目(038000546317504) |
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| 摘 要： | 在交通部治理公路超限运输的背景下,本文研究了乘用车物流企业多式联运模式下的网络优化问题,以运输网络总成本最小为目标,考虑物流时效、枢纽节点容量及规模经济效应等因素,构建了基于轴辐式理论的运输网络优化模型,提出了混合智能优化算法。针对多参数多水平的寻优问题,对模型的三个关键输入参数,即枢纽节点数量、枢纽节点容量和规模效应折扣系数,引入正交试验方法,降低求解多参数多水平寻优问题的工作量,为确定各参数合理取值提供了新的途径。研究结果表明:枢纽节点容量、折扣系数与枢纽数量三个输入参数对优化结果的影响具有主次顺序,影响程度依次减弱,而且只有枢纽节点容量与折扣系数对乘用车运输网络总效益的影响起显著作用。采用混合轴辐式的网络结构与多式联运的运输组织模式进行优化后的运输网络,相对于原有“点对点”公路运输网络总成本减少10%,从运营管理与成本控制两方面均可有效应对公路治超带来的风险。
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| 关 键 词： | 轴辐式理论 运输网络优化 混合智能优化算法 正交试验 乘用车运输网络 |
| 收稿时间： | 2017-08-27 |
Optimization Method of Passenger Vehicle Transportation Network Based on Orthogonal Experimental |
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| QIN Lu,LIU Hong-chao,SUN Zhi-yuan.Optimization Method of Passenger Vehicle Transportation Network Based on Orthogonal Experimental[J].Operations Research and Management Science,2018,27(12):38-46. |
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| Authors: | QIN Lu LIU Hong-chao SUN Zhi-yuan |
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| Affiliation: | 1.School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044,China;2.Zhong Wu XieBeijing Logistics Engineering Design Institute, Beijing 100834, China;3.College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China |
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| Abstract: | In the context of the Ministry of Transportation to control the road overrun transport, this paper studies the problem of network optimization under multimodal transport mode of passenger vehicle logistics enterprises, and taking the minimum cost of transportation network as the goal, taking into account the logistics timeliness, hub node capacity and economies of scale and other factors, the transportation network optimization model is established based on hub and spoke theory, and a hybrid intelligent optimization algorithm is proposed. Orthogonal test is designed to solve the problem of multi parameter and multi-level optimization, and the three key input parameters of model are hub node number, hub node capacity and scale effect discount coefficient, which effectively reduces the solving multiple parameters level optimization problem of work, and it provides a new way to determine the reasonable values of each parameter. The results show that: Hub node capacity, discount coefficient and hub number, the three input parameters have the order of influence on optimization results, and the degree of influence decreases successively; moreover, only the hub node capacity and discount coefficient play a significant role in the total benefit of passenger vehicle transportation network. And a hybrid hub and spoke network structure and multimodal transport organization model are used to optimize the transportation network, and compared with the original “point to point” road transportation network, the total cost is reduced by 10%, so that it can effectively deal with the risks of administering highway overload both in operation management and cost control. |
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| Keywords: | hub and spoke theory transportation network optimization hybrid intelligent optimization algorithm Orthogonal test passenger vehicle transportation network |
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