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

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 runnin...

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Main Authors: Jianming Yao, Mengjie Gu
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/519125
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spelling doaj-7e34d110c3464a4db94b235ad858b8592020-11-24T23:01:24ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/519125519125Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service ModeJianming Yao0Mengjie Gu1School of Business, Renmin University of China, Beijing 100872, ChinaSchool of Business, Renmin University of China, Beijing 100872, ChinaFor 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.http://dx.doi.org/10.1155/2015/519125
collection DOAJ
language English
format Article
sources DOAJ
author Jianming Yao
Mengjie Gu
spellingShingle Jianming Yao
Mengjie Gu
Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode
Mathematical Problems in Engineering
author_facet Jianming Yao
Mengjie Gu
author_sort Jianming Yao
title Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode
title_short Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode
title_full Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode
title_fullStr Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode
title_full_unstemmed Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode
title_sort optimization analysis of supply chain resource allocation in customized online shopping service mode
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description 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.
url http://dx.doi.org/10.1155/2015/519125
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AT mengjiegu optimizationanalysisofsupplychainresourceallocationincustomizedonlineshoppingservicemode
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