An integration of AHP approach and Bayes classification algorithm in supplier selection

Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/38153

Title:	An integration of AHP approach and Bayes classification algorithm in supplier selection
Authors:	Chan, FTS Chung, SH Chow, JCL Niu, B
Issue Date:	2013
Source:	The 2013 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Bangkok, Thailand, 10-13 December 2013, p. 216-220 (CD)
Abstract:	Weight of criteria can only be changed through discussion or analysis of experts under traditional supplier selection method, which brings up two problems: (1) human effect problem and (2) incapability in timely decision making on updates of weights. In this paper, a new supplier selection method based on integration of Analytic Hierarchy Process, the Bayesian Classifier Algorithm and dynamic probabilities (AHP-BCA) is proposed. The method makes predictions with the probabilities of occurrences of criteria values based on historical records to avoid any human effects in decision making. It is also equipped with an instant self-update function to instantly update the probability values with new data, and be ready for next calculation. A simulation experiment is conducted to compare the performance of the proposed approach with a remarkable traditional approach in literature with historical data. Results show that the proposed approach can outperform the traditional one in achieving better selection results.
Keywords:	Analytic hierarchy process Bayesian algorithm Supplier selection
DOI:	10.1109/IEEM.2013.6962406
Appears in Collections:	Conference Paper

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