Approximation quality for sorting rules
Computational Statistics & Data Analysis
A hybrid approach to supplier selection for the maintenance of a competitive supply chain
Expert Systems with Applications: An International Journal
Dominance-based rough set approach and knowledge reductions in incomplete ordered information system
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy hierarchical TOPSIS for supplier selection
Applied Soft Computing
Expert Systems with Applications: An International Journal
Discernibility matrix simplification for constructing attribute reducts
Information Sciences: an International Journal
An novel approach to supplier selection based on vague sets group decision
Expert Systems with Applications: An International Journal
Monotonic Variable Consistency Rough Set Approaches
International Journal of Approximate Reasoning
A study of using RST to create the supplier selection model and decision-making rules
Expert Systems with Applications: An International Journal
Supplier selection and order allocation based on fuzzy SWOT analysis and fuzzy linear programming
Expert Systems with Applications: An International Journal
A weighted additive fuzzy programming approach for multi-criteria supplier selection
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
A new intuitionistic fuzzy rough set approach for decision support
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
Application of decision-making techniques in supplier selection: A systematic review of literature
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
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.