Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/42937
Title: A novel believable rough set approach for supplier selection
Authors: Chai, J
Liu, JNK
Keywords: Logistics and supply chain management
Multiple criteria decision analysis
Rule-based approach
Human preference
Issue Date: 2014
Publisher: Pergamon Press
Source: Expert systems with applications, 2014, v. 41, no. 1, p. 92-104 How to cite?
Journal: Expert systems with applications 
Abstract: We consider the issue of supplier selection by using rule-based methodology. Supplier Selection (SS) is an important activity in Logistics and Supply Chain Management in today's global market. It is one of major applications of Multiple Criteria Decision Analysis (MCDA) that concerns about preference-related decision information. The rule-based methodology is proven of its effectiveness in handling preference information and performs well in sorting or ranking alternatives. However, how to utilize them in SS still remains open for more studies. In this paper, we propose a novel Believable Rough Set Approach (BRSA). This approach performs the complete problem-solving procedures including (1) criteria analysis, (2) rough approximation, (3) decision rule induction, and (4) a scheme for rule application. Unlike other rule-based solutions that just extract certain information, the proposed solution additionally extracts valuable uncertain information for rule induction. Due to such mechanism, BRSA outperforms other solutions in evaluation of suppliers. A detailed empirical study is provided for demonstration of decision-making procedures and multiple comparisons with other proposals.
URI: http://hdl.handle.net/10397/42937
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2013.07.014
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