"The Last Kilometer" Network Optimization Research of E-Commerce

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Abstract:

In this paper we present a series of more rigorous steps, using a location model and take into account the actual roads’ condition, rents and other relevant factors to solve the network location problem. And we put forward a new idea to solve the "the last kilometer" problem of e-commerce’s network optimization.

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224-227

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Wang Z, Yao D Q, Huang P. A new location-inventory policy with reverse logistics applied to B2C e-markets of China[J]. International Journal of Production Economics, 2007, 107(2): 350-363.

DOI: 10.1016/j.ijpe.2006.09.012

Google Scholar

[2] Wang Zheng-cheng. Design and Realization of Logistics Management System Based on E-Commerce[J]. Journal of Zhejiang Institute of Science and Technology, 2004, 21(4): 342-345. (In Chinese).

Google Scholar

[3] Klose A, Drexl A. Facility location models for distribution system design[J]. European Journal of Operational Research, 2005, 162(1): 4-29.

DOI: 10.1016/j.ejor.2003.10.031

Google Scholar

[4] Jayaraman V, Ross A. A simulated annealing methodology to distribution network design and management[J]. European Journal of Operational Research, 2003, 144(3): 629-645.

DOI: 10.1016/s0377-2217(02)00153-4

Google Scholar

[5] Weltevreden J W J. B2c e-commerce logistics: the rise of collection-and-delivery points in The Netherlands[J]. International Journal of Retail & Distribution Management, 2008, 36(8): 638-660.

DOI: 10.1108/09590550810883487

Google Scholar

[6] Weltevreden J W J, Rotem-Mindali O. Mobility effects of b2c and c2c e-commerce in the Netherlands: a quantitative assessment[J]. Journal of Transport Geography, 2009, 17(2): 83-92.

DOI: 10.1016/j.jtrangeo.2008.11.005

Google Scholar

[7] Zhao Y. Double populations genetic algorithm for vehicle routing problem[J]. COMPUTER INTEGRATED MANUFACTURING SYSTEMS-BEIJING-, 2004, 10(3): 303-306.

Google Scholar