发表状态 | 已发表Published |
题名 | A novel believable rough set approach for supplier selection |
作者 | |
发表日期 | 2014 |
发表期刊 | Expert Systems with Applications
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ISSN/eISSN | 0957-4174 |
卷号 | 41期号:1页码:92-104 |
摘要 | 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. |
关键词 | Human preference Logistics and supply chain management Multiple criteria decision analysis Rule-based approach |
DOI | 10.1016/j.eswa.2013.07.014 |
URL | 查看来源 |
收录类别 | SCIE |
语种 | 英语English |
WOS研究方向 | Computer Science ; Engineering ; Operations Research & Management Science |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science |
WOS记录号 | WOS:000326214800010 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/4720 |
专题 | 个人在本单位外知识产出 |
通讯作者 | Chai, Junyi |
作者单位 | Department of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong |
推荐引用方式 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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