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Mathematical Problems in Engineering
Volume 2015, Article ID 519125, 11 pages
Research Article

Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode

School of Business, Renmin University of China, Beijing 100872, China

Received 3 June 2014; Revised 3 September 2014; Accepted 11 September 2014

Academic Editor: Xingsheng Gu

Copyright © 2015 Jianming Yao and Mengjie Gu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


For an online-shopping company, whether it can provide its customers with customized service is the key to enhance its customers’ experience value and its own competence. A good customized service requires effective integration and reasonable allocation of the company’s supply chain resources running in the background. Based on the analysis of the allocation of supply chain resources in the customized online shopping service mode and its operational characteristics, this paper puts forward an optimization model for the resource allocation and builds an improved ant algorithm to solve it. Finally, the effectiveness and feasibility of the optimization method and algorithm are demonstrated by a numerical simulation. This paper finds that the special online shopping environments lead to many dynamic and uncertain characters of the service demands. Different customized service patterns and their combination patterns should match with different supply chain resource allocations. The optimization model not only reflects the required service cost and delivery time in the objective function, but also considers the service scale effect optimization and the relations of integration benefits and risks. The improved ant algorithm has obvious advantages in flexibly balancing the multiobjective optimizations, adjusting the convergence speed, and adjusting the operation parameters.