Optimization based transportation service trading in B2B e-commerce logistics

Mengdi Zhang, George Q. Huang (), Su Xiu Xu and Zhiheng Zhao
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Mengdi Zhang: The University of Hong Kong
George Q. Huang: The University of Hong Kong
Su Xiu Xu: Jinan University
Zhiheng Zhao: The University of Hong Kong

Journal of Intelligent Manufacturing, 2019, vol. 30, issue 7, No 3, 2603-2619

Abstract: Abstract This paper addresses the e-commerce transportation service trading (ETST) problem in B2B e-commerce. ETST determines and optimizes the matching issue between the sets of online orders generated by the e-commerce platform and the sets of transport vehicles supplied by logistics service providers. We first establish a framework for formulating ETST problem with the consideration of its characteristics. We then apply the framework for developing a cost minimization model to optimize the assignment of B2B online orders and vehicles. A full-factorial simulation experiment is proposed to investigate the effects of factors on the performance indexes such as the total logistics cost per unit, the type of the vehicle required, and the number of the vehicle in use. The results show that the vehicle cost and order characteristics (ratio of weight and volume) significantly impact the vehicle assignment in terms of the vehicle type and vehicle quantity. We also find that the ratio of different vehicles is significantly affected by demand fluctuations and holding cost.

Keywords: E-commerce logistics; Transportation service procurement; Vehicle assignment; Global optimization; Designed experiments; Analysis of variance (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10845-016-1287-x

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