Clustering framework for Supply Chain Management (SCM) system

Danish Irfan; Xiaofei Xu; Shengchun Deng; Imran Ali Khan

doi:10.1109/DMAMH.2007.4414591

Clustering framework for Supply Chain Management (SCM) system

Danish Irfan^*
, Xiaofei Xu
, Shengchun Deng
, Imran Ali Khan

^*Corresponding author for this work

IEEE
School of Computer Science and Technology, Harbin Institute of Technology
COMSATS University Islamabad
Chinese Academy of Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

The cram of supply chain management (SCM) is being considered as center of attention and motivation, not only among academics but also among practitioners in recent years. SCM systems face complexity, process's time compression, and lack ness of process optimization. In our current work, we present a broad framework for SCM, based on K-means clustering algorithm which concentrates on the supply chain (SC) processes for lessen the complexity, optimization factors in SC process communication, product variability and inaccurate forecast. Results show a feasibility to adopt this technique from a business analyst view point.

Original language	English
Title of host publication	Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007
Pages	422-426
Number of pages	5
DOIs	https://doi.org/10.1109/DMAMH.2007.4414591
State	Published - 2007
Externally published	Yes
Event	2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007 - Chongqing, China Duration: 10 Dec 2007 → 12 Dec 2007

Publication series

Name	Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007

Conference

Conference	2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007
Country/Territory	China
City	Chongqing
Period	10/12/07 → 12/12/07

Access to Document

10.1109/DMAMH.2007.4414591

Cite this

Irfan, D., Xu, X., Deng, S., & Khan, I. A. (2007). Clustering framework for Supply Chain Management (SCM) system. In Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007 (pp. 422-426). Article 4414591 (Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007). https://doi.org/10.1109/DMAMH.2007.4414591

@inproceedings{3bd664ca50274d018610c691dd6d069f,

title = "Clustering framework for Supply Chain Management (SCM) system",

abstract = "The cram of supply chain management (SCM) is being considered as center of attention and motivation, not only among academics but also among practitioners in recent years. SCM systems face complexity, process's time compression, and lack ness of process optimization. In our current work, we present a broad framework for SCM, based on K-means clustering algorithm which concentrates on the supply chain (SC) processes for lessen the complexity, optimization factors in SC process communication, product variability and inaccurate forecast. Results show a feasibility to adopt this technique from a business analyst view point.",

author = "Danish Irfan and Xiaofei Xu and Shengchun Deng and Khan, \{Imran Ali\}",

year = "2007",

doi = "10.1109/DMAMH.2007.4414591",

language = "英语",

isbn = "0769530656",

series = "Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007",

pages = "422--426",

booktitle = "Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007",

note = "2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007 ; Conference date: 10-12-2007 Through 12-12-2007",

}

Irfan, D, Xu, X, Deng, S & Khan, IA 2007, Clustering framework for Supply Chain Management (SCM) system. in Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007., 4414591, Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007, pp. 422-426, 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007, Chongqing, China, 10/12/07. https://doi.org/10.1109/DMAMH.2007.4414591

Clustering framework for Supply Chain Management (SCM) system. / Irfan, Danish; Xu, Xiaofei; Deng, Shengchun et al.
Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007. 2007. p. 422-426 4414591 (Proceedings - 2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - The cram of supply chain management (SCM) is being considered as center of attention and motivation, not only among academics but also among practitioners in recent years. SCM systems face complexity, process's time compression, and lack ness of process optimization. In our current work, we present a broad framework for SCM, based on K-means clustering algorithm which concentrates on the supply chain (SC) processes for lessen the complexity, optimization factors in SC process communication, product variability and inaccurate forecast. Results show a feasibility to adopt this technique from a business analyst view point.

AB - The cram of supply chain management (SCM) is being considered as center of attention and motivation, not only among academics but also among practitioners in recent years. SCM systems face complexity, process's time compression, and lack ness of process optimization. In our current work, we present a broad framework for SCM, based on K-means clustering algorithm which concentrates on the supply chain (SC) processes for lessen the complexity, optimization factors in SC process communication, product variability and inaccurate forecast. Results show a feasibility to adopt this technique from a business analyst view point.

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SN - 9780769530659

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Y2 - 10 December 2007 through 12 December 2007

ER -

Clustering framework for Supply Chain Management (SCM) system

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