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K-means algorithm in the shop purchasing point of application of choice

Author: YeZongYun
Tutor: ZhangZiGang
School: Huazhong University of Science and Technology
Course: Logistics Engineering
Keywords: E-commerce Purchasing point k-means Site planning Cluster analysis Logistics nodes
CLC: F224
Type: Master's thesis
Year: 2011
Downloads: 74
Quote: 0
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Abstract


E-commerce development to people's lives has brought great convenience also brings many challenges , so it was predicted that online shopping combined with community storefront online shopping is the future trend , it is a good solution because shopping security issues , payment issues and service issues , purchasing point model is one of the best . But the contradiction is universal, purchasing point brought new problems , including management fees increased purchasing point their poor stability . E-commerce companies want to better carry out their business , better play the advantages of purchasing point , you must perform any necessary planning purchasing point . People long for siting studies , and achieved fruitful results. Cluster analysis method is widely applied to all walks of study, including field applied to facility location . This paper combines the case , the application of cluster analysis methods k-means algorithm purchasing point selection research. Paper first outlines the development of e-commerce and e-commerce logistics situation , outlining the characteristics of purchasing point , recalling the location problem , cluster analysis research status and current domestic purchasing point of the general situation , this study demonstrated the significance of this study and propose objectives and research methods. Secondly, the customer demand characteristics are outlined on the purchasing point selection objectives and constraints study show initial k-means algorithm selection in purchasing point of principle , it is the key attributes of alternative purchasing point for refining , and these key attributes as well as numerical similarity measure . Then , the system summarizes the application of k-means clustering algorithm for the general process , showing the application of k-means algorithm selection problem with purchasing point matching process. Finally, 2688 e-commerce company purchasing point of choice, application software for purchasing this point more classic case study conducted to obtain the clustering results and the results were some analysis .

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CLC: > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods
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