C2C环境下配送中心的选址问题研究
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摘要
由C2C电子商务平台企业建设自有配送中心、第三方物流协助配送是近期刚被提出的C2C环境下的新型配送模式,是对现有C2C电子商务配送方式的革新。目前C2C环境下的配送完全依赖第三方物流,而我国第三方物流还不够成熟,成为了C2C电子商务进一步发展的瓶颈。为了尽快克服瓶颈问题,本文以C2C平台企业建设自有配送中心的设想为背景,展开了对C2C环境下配送中心选址问题的研究。
本文首先分析了C2C环境下建设自有配送中心的必要性。我国现有电子商务的配送模式存在配送效率、配送容量、仓储管理等方面的局限性。由C2C平台企业建设自有配送中心,不仅可以克服这些局限性,还可以节约整体分销成本,因而在C2C环境下建设自有配送中心很有意义。
本文然后构建了C2C环境下的配送中心选址模型。通过对选址影响因素的分析,提出了在C2C环境下仓储规模效益的不可被忽略性。结合选址模型的影响因素,本文以分段线性函数代表仓储成本描述并构建了适用于在区域内进行首次选址规划的“初次选址”模型,及适用于应对需求增长的“二次选址”模型。
之后,本文在分支定界法及Efroymson-Ray算法的基础上,利用Efroymson-Ray的优化思想,设计了一种针对C2C选址模型的改进算法。该算法能够解决基于仓储规模效益的选址问题。
最后,本文对设计出的改进算法进行了有效性验证和性能分析,并将算法应用到淘宝网的选址模型中,求解出了具有说服力的结果。
A new distribution mode was proposed recently, which requires C2C companies to establish several self-owned distribution centers and get transportation service from third party logistics. The new mode is quite different from the distribution mode which C2C companies apply currently. In the current distribution mode, third party logistics take fully responsibility for all the distribution work of C2C companies. And because of the underdevelopment of China’s third party logistics, C2C companies in China are now suffering development bottleneck from distribution issues. According to the setting, this paper discussed the distribution center location problem under C2C e-commerce.
Firstly, the paper analyzed the necessity of the self-owned DC establishment. The current distribution mode has several shortages in the aspect of distribution efficiency, distribution capacity and warehouse management. The new mode can not only conquer these shortages, but also save more cost. Thus, it is profitable to establish self-owned DCs by C2C companies.
Then, the paper proposed two operations research models for the location problem. One model will be used for the first time location planning when there are no DCs in the area, while the other will be used to plan more DCs in the area in order to solve the capacity shortage problem led by increasing demand. These two models will consider the economies of scale of warehousing and will use piecewise function to represent the scale effect.
After that, an advanced algorithm was designed to solve the location problem with the economies of scale. This algorithm was based on the Efroymson-Ray branch and bound algorithm, which was an optimization algorithm for the original branch and bound.
Finally, the modified algorithm was tested by several experiments and proved with accuracy and efficiency. A real distribution center location problem from taobao.com was then solved by the advanced algorithm and got reasonable solution.
本文首先分析了C2C环境下建设自有配送中心的必要性。我国现有电子商务的配送模式存在配送效率、配送容量、仓储管理等方面的局限性。由C2C平台企业建设自有配送中心,不仅可以克服这些局限性,还可以节约整体分销成本,因而在C2C环境下建设自有配送中心很有意义。
本文然后构建了C2C环境下的配送中心选址模型。通过对选址影响因素的分析,提出了在C2C环境下仓储规模效益的不可被忽略性。结合选址模型的影响因素,本文以分段线性函数代表仓储成本描述并构建了适用于在区域内进行首次选址规划的“初次选址”模型,及适用于应对需求增长的“二次选址”模型。
之后,本文在分支定界法及Efroymson-Ray算法的基础上,利用Efroymson-Ray的优化思想,设计了一种针对C2C选址模型的改进算法。该算法能够解决基于仓储规模效益的选址问题。
最后,本文对设计出的改进算法进行了有效性验证和性能分析,并将算法应用到淘宝网的选址模型中,求解出了具有说服力的结果。
A new distribution mode was proposed recently, which requires C2C companies to establish several self-owned distribution centers and get transportation service from third party logistics. The new mode is quite different from the distribution mode which C2C companies apply currently. In the current distribution mode, third party logistics take fully responsibility for all the distribution work of C2C companies. And because of the underdevelopment of China’s third party logistics, C2C companies in China are now suffering development bottleneck from distribution issues. According to the setting, this paper discussed the distribution center location problem under C2C e-commerce.
Firstly, the paper analyzed the necessity of the self-owned DC establishment. The current distribution mode has several shortages in the aspect of distribution efficiency, distribution capacity and warehouse management. The new mode can not only conquer these shortages, but also save more cost. Thus, it is profitable to establish self-owned DCs by C2C companies.
Then, the paper proposed two operations research models for the location problem. One model will be used for the first time location planning when there are no DCs in the area, while the other will be used to plan more DCs in the area in order to solve the capacity shortage problem led by increasing demand. These two models will consider the economies of scale of warehousing and will use piecewise function to represent the scale effect.
After that, an advanced algorithm was designed to solve the location problem with the economies of scale. This algorithm was based on the Efroymson-Ray branch and bound algorithm, which was an optimization algorithm for the original branch and bound.
Finally, the modified algorithm was tested by several experiments and proved with accuracy and efficiency. A real distribution center location problem from taobao.com was then solved by the advanced algorithm and got reasonable solution.
引文
[1]刘金明,王耀球.中美物流成本占GDP的对比分析[N].现代物流报,2005-09-15(2).
[2]中国互联网络信息中心.第29次中国互联网络发展状况调查统计报告[R]. 2012:31-33.
[3] Hau L. Lee, Seungjin Whang. Winning the Last Mile of E-commerce[J]. MIT Sloan Management Review. Summer 2001:54-58.
[4]汤浅和夫. IT物流[M].上海:文汇出版社. 2002:12-13.
[5] Kent N. Gourdin.全球物流管理[M].北京:人民邮件出版社. 2002:105-106.
[6]黄鹏霄,庄英.击碎电子商务中的物流瓶颈[J].中外科技信息,2000(6):42-47.
[7]王法野.对电子商务中物流瓶颈的探讨[J].科技与管理,2003(4):128-129.
[8] Termessee State University. Research of TPL[J]. The Journal of Business,2003:10-18.
[9]谭胜.电子商务物流配送的组织形式、方法与策略[D].西南财经大学,2001.
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[11] Fridrich C.J. Alfred Weber’s Theory of the Location of Industries (Translation)[M]. University of Chicago Press, Illinois, USA. 1929.
[12] Revelle C, Marks D & Liebman JC. An Analysis of Private and Public Sector Location Models[J]. Management Science,1970(16):692-707.
[13] Cooper L. Location-allocation problems[J]. Operations Research,1963(11):331-343.
[14] Kuhn AA, Kuenne R. An Efficient Algorithm for the Numerical Solutions of the Generalized Weber Problem in Spatial Economics[J]. Journal of Regional Science,1962(4):21-28.
[15] Efroymson M & Ray TL. A Branch-Bound Algorithm for Plant Location[J]. Operations Research,1966(14):361-368.
[16] Khumawala BM. An Efficient Branch and Bound Algorithm for the Warehouse Location Problem[J]. Management Science,1972(18B):718-731.
[17] Pirkul H, Jayaraman V. A Multi-commodity, Multi-plant, Capacitated Facility Location Problem: Formulation and Efficient Heuristic Solution[J]. Computers & Operations Research, 1998(25): 869-878.
[18] Singh KN, Oudheusden Dirk. A Branch and Bound Algorithm for the Traveling Purchaser Problem[J]. European Journal of Operational Research,1997(97):571-579.
[19]胥文华.基于供应链的奥运物流中心选址研究[D].北京交通大学,2008.
[20]杨志. ABC公司物流配送中心选址规划[D].清华大学,2008.
[21]李莹.供应链选址模型的改进及其在制造业中的应用研究[D].首都经济贸易大学,2008.
[22]罗提.马云投资千亿做物流拟在全国七大区域建仓储[N].华西都市报,2011-01-21(32).
[23]章炳林. C2C电子商务的物流配送问题研究[D].合肥工业大学,2008.
[24]林建敏.资金“断血”网上超市纷纷夭折[N].信息时报,2011-10-26(D2).
[25]胡运权.运筹学教程[M].北京:清华大学出版社. 2003:137-139.
[26]胡运权.运筹学教程[M].北京:清华大学出版社. 2003:21-23.
[27]李欣,关志民,高俊俊.电子商务环境下企业物流配送模式的选择[J].郑州航空工业管理学院学报,2003,21(4):123-125.
[28]高斌,张仁颐.物流中心选址的一种新模型[J].物流科技,2003,26(99):4-6.
[29]王晓博.电子商务下物流配送系统优化模型和算法研究[D].哈尔滨工业大学,2008.
[30]耿伟.电子商务环境下的我国物流配送研究[J].中国市场,2008(1):114-115.
[31]姜大元.基于多节点的物流选址规划研究[J].铁道运输经济,2005,27(8):24-26.
[32] Aikens C.H. Facility Location Models for Distribution Planning[J]. European Journal of Operational Research,1985, 22(2):263-279.
[33] Taniguchi E.Optimal Size and Location Planning of Public Logistics Terminals [J] .Transportation Research, 1999, 35E:207-222.
[34]魏巧云.物流配送中心选址模型及其启发式算法[J].交通运输工程学报,2003(3):65-68.
[35]刘海燕,李宗平,叶怀珍.物流配送中心选址模型[J].西南交通大学学报,2000, 35(3):311-314.
[36]徐杰,田源,汝宜红.物流中心选址的影响因素分析及案例[J].物流技术, 2002,(2): 28-31.
[37]刘志硕.智能物流系统理论与方法研究[D].北京交通大学,2004.
[38]龚延成,郭晓汾,蔡团结,李卫江.物流配送点选址模型及其算法研究[J].中国管理科学,2003,16(2):123-126.
[39]胡刚,王淑琴.针对第三方物流企业的物流中心选址模型研究[J].公路交通与科技,2002, 1(12):172—176.
[40]蔡临宁.物流系统规划——建模及实例分析[M].北京:机械工业出版社,2003:23-58.
[41]谭凌.从于库存优化的配送中心选址问题研究[J].系统工程学报,2004,19(1):59-65.
[2]中国互联网络信息中心.第29次中国互联网络发展状况调查统计报告[R]. 2012:31-33.
[3] Hau L. Lee, Seungjin Whang. Winning the Last Mile of E-commerce[J]. MIT Sloan Management Review. Summer 2001:54-58.
[4]汤浅和夫. IT物流[M].上海:文汇出版社. 2002:12-13.
[5] Kent N. Gourdin.全球物流管理[M].北京:人民邮件出版社. 2002:105-106.
[6]黄鹏霄,庄英.击碎电子商务中的物流瓶颈[J].中外科技信息,2000(6):42-47.
[7]王法野.对电子商务中物流瓶颈的探讨[J].科技与管理,2003(4):128-129.
[8] Termessee State University. Research of TPL[J]. The Journal of Business,2003:10-18.
[9]谭胜.电子商务物流配送的组织形式、方法与策略[D].西南财经大学,2001.
[10]夏丽萍.我国电子商务进程中的物流瓶颈分析[J].经济师,2005(5):122-123.
[11] Fridrich C.J. Alfred Weber’s Theory of the Location of Industries (Translation)[M]. University of Chicago Press, Illinois, USA. 1929.
[12] Revelle C, Marks D & Liebman JC. An Analysis of Private and Public Sector Location Models[J]. Management Science,1970(16):692-707.
[13] Cooper L. Location-allocation problems[J]. Operations Research,1963(11):331-343.
[14] Kuhn AA, Kuenne R. An Efficient Algorithm for the Numerical Solutions of the Generalized Weber Problem in Spatial Economics[J]. Journal of Regional Science,1962(4):21-28.
[15] Efroymson M & Ray TL. A Branch-Bound Algorithm for Plant Location[J]. Operations Research,1966(14):361-368.
[16] Khumawala BM. An Efficient Branch and Bound Algorithm for the Warehouse Location Problem[J]. Management Science,1972(18B):718-731.
[17] Pirkul H, Jayaraman V. A Multi-commodity, Multi-plant, Capacitated Facility Location Problem: Formulation and Efficient Heuristic Solution[J]. Computers & Operations Research, 1998(25): 869-878.
[18] Singh KN, Oudheusden Dirk. A Branch and Bound Algorithm for the Traveling Purchaser Problem[J]. European Journal of Operational Research,1997(97):571-579.
[19]胥文华.基于供应链的奥运物流中心选址研究[D].北京交通大学,2008.
[20]杨志. ABC公司物流配送中心选址规划[D].清华大学,2008.
[21]李莹.供应链选址模型的改进及其在制造业中的应用研究[D].首都经济贸易大学,2008.
[22]罗提.马云投资千亿做物流拟在全国七大区域建仓储[N].华西都市报,2011-01-21(32).
[23]章炳林. C2C电子商务的物流配送问题研究[D].合肥工业大学,2008.
[24]林建敏.资金“断血”网上超市纷纷夭折[N].信息时报,2011-10-26(D2).
[25]胡运权.运筹学教程[M].北京:清华大学出版社. 2003:137-139.
[26]胡运权.运筹学教程[M].北京:清华大学出版社. 2003:21-23.
[27]李欣,关志民,高俊俊.电子商务环境下企业物流配送模式的选择[J].郑州航空工业管理学院学报,2003,21(4):123-125.
[28]高斌,张仁颐.物流中心选址的一种新模型[J].物流科技,2003,26(99):4-6.
[29]王晓博.电子商务下物流配送系统优化模型和算法研究[D].哈尔滨工业大学,2008.
[30]耿伟.电子商务环境下的我国物流配送研究[J].中国市场,2008(1):114-115.
[31]姜大元.基于多节点的物流选址规划研究[J].铁道运输经济,2005,27(8):24-26.
[32] Aikens C.H. Facility Location Models for Distribution Planning[J]. European Journal of Operational Research,1985, 22(2):263-279.
[33] Taniguchi E.Optimal Size and Location Planning of Public Logistics Terminals [J] .Transportation Research, 1999, 35E:207-222.
[34]魏巧云.物流配送中心选址模型及其启发式算法[J].交通运输工程学报,2003(3):65-68.
[35]刘海燕,李宗平,叶怀珍.物流配送中心选址模型[J].西南交通大学学报,2000, 35(3):311-314.
[36]徐杰,田源,汝宜红.物流中心选址的影响因素分析及案例[J].物流技术, 2002,(2): 28-31.
[37]刘志硕.智能物流系统理论与方法研究[D].北京交通大学,2004.
[38]龚延成,郭晓汾,蔡团结,李卫江.物流配送点选址模型及其算法研究[J].中国管理科学,2003,16(2):123-126.
[39]胡刚,王淑琴.针对第三方物流企业的物流中心选址模型研究[J].公路交通与科技,2002, 1(12):172—176.
[40]蔡临宁.物流系统规划——建模及实例分析[M].北京:机械工业出版社,2003:23-58.
[41]谭凌.从于库存优化的配送中心选址问题研究[J].系统工程学报,2004,19(1):59-65.