Status | 已发表Published |
Title | A novel believable rough set approach for supplier selection |
Creator | |
Date Issued | 2014 |
Source Publication | Expert Systems with Applications
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ISSN | 0957-4174 |
Volume | 41Issue: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. |
Keyword | Human preference Logistics and supply chain management Multiple criteria decision analysis Rule-based approach |
DOI | 10.1016/j.eswa.2013.07.014 |
URL | View source |
Indexed By | SCIE |
Language | 英语English |
WOS Research Area | Computer Science ; Engineering ; Operations Research & Management Science |
WOS Subject | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science |
WOS ID | WOS:000326214800010 |
Citation statistics | |
Document Type | Journal article |
Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/4720 |
Collection | Research outside affiliated institution |
Corresponding Author | Chai, 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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