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Status已发表Published
TitleA novel believable rough set approach for supplier selection
Creator
Date Issued2014
Source PublicationExpert Systems with Applications
ISSN0957-4174
Volume41Issue:1Pages:92-104
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. © 2013 Elsevier Ltd. All rights reserved.

KeywordHuman preference Logistics and supply chain management Multiple criteria decision analysis Rule-based approach
DOI10.1016/j.eswa.2013.07.014
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaComputer Science ; Engineering ; Operations Research & Management Science
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS IDWOS:000326214800010
Citation statistics
Cited Times:33[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/4720
CollectionResearch outside affiliated institution
Corresponding AuthorChai, Junyi
Affiliation
Department of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Recommended Citation
GB/T 7714
Chai, Junyi,Liu, James Nga Kwok. A novel believable rough set approach for supplier selection[J]. Expert Systems with Applications, 2014, 41(1): 92-104.
APA Chai, Junyi, & Liu, James Nga Kwok. (2014). A novel believable rough set approach for supplier selection. Expert Systems with Applications, 41(1), 92-104.
MLA Chai, Junyi,et al."A novel believable rough set approach for supplier selection". Expert Systems with Applications 41.1(2014): 92-104.
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