Title: Hybrid-LWM: A linear-model based hybrid clustering algorithm for supplier categorisation

Authors: Danish Irfan; Deng Shengchun; Xu Xiaofei

Addresses: Harbin Institute of Technology, School of Computer Science and Technology, P.O. Box #315, HIT, No. 92, West Dazhi Street, Nangang District, Harbin 150001, China. ' Harbin Institute of Technology, School of Computer Science and Technology, P.O. Box #315, HIT, No. 92, West Dazhi Street, Nangang District, Harbin 150001, China. ' Harbin Institute of Technology, School of Computer Science and Technology, P.O. Box #315, HIT, No. 92, West Dazhi Street, Nangang District, Harbin 150001, China

Abstract: Supplier categorisation is a key step in Supplier Base Management (SBM), which is considered as a business strategy to reduce the logistic costs and improve business performance. In this work, we present projected clustering-based algorithm combined with Linear Weighted Model (LWM) for categorisation of suppliers in supply base management. We applied this hybrid approach for data set of suppliers in a supplier base.

Keywords: supplier categorisation; linear weighted models; modelling; data mining; data clustering; supplier base management; hybrid clustering; supplier classification; logistics; supply chain management; SCM; suppliers.

DOI: 10.1504/IJSCC.2011.042433

International Journal of Systems, Control and Communications, 2011 Vol.3 No.3, pp.270 - 279

Published online: 11 Sep 2011 *

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