2022
DOI: 10.3390/axioms11060275
|View full text |Cite
|
Sign up to set email alerts
|

A Novel Multi-Criteria Decision-Making Method Based on Rough Sets and Fuzzy Measures

Abstract: Rough set theory provides a useful tool for data analysis, data mining and decision making. For multi-criteria decision making (MCDM), rough sets are used to obtain decision rules by reducing attributes and objects. However, different reduction methods correspond to different rules, which will influence the decision result. To solve this problem, we propose a novel method for MCDM based on rough sets and a fuzzy measure in this paper. Firstly, a type of non-additive measure of attributes is presented by the im… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
13
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
10

Relationship

2
8

Authors

Journals

citations
Cited by 26 publications
(13 citation statements)
references
References 51 publications
0
13
0
Order By: Relevance
“…In the future, we will continue to study partial residuated lattices and their special subclasses, and reveal the internal relationship between partial residuated lattices (regular partial residuated lattices) and other logical algebras [21][22][23]. In addition, we will study fuzzy reasoning and fuzzy rough sets based on partial residuated lattices, as well as other applications [24][25][26].…”
Section: Discussionmentioning
confidence: 99%
“…In the future, we will continue to study partial residuated lattices and their special subclasses, and reveal the internal relationship between partial residuated lattices (regular partial residuated lattices) and other logical algebras [21][22][23]. In addition, we will study fuzzy reasoning and fuzzy rough sets based on partial residuated lattices, as well as other applications [24][25][26].…”
Section: Discussionmentioning
confidence: 99%
“…In addition, considering non-commutative fuzzy logic, the non-commutative generalization of weak IBL-algebras is also worth studying, which is what we are doing. Moreover, as an interesting research topic, we can consider a new model of fuzzy rough sets (see [26][27][28]) based on inflationary (pseudo-) general residuated lattices.…”
Section: Discussionmentioning
confidence: 99%
“…Huang et al used interval numbers to represent the attribute information in the group decision matrix, and then proposed a distributed interval weighted average operator to integrate qualitative data and quantitative judgments; then, they defined relevant operation rules, and finally ranked and selected the best green suppliers [34]. To solve the problem that different approximation methods for rough sets affect the results, Wang et al first proposed an attribute metric method based on fuzzy sets, and then constructed Choquet integral operators based on the attribute metric and matching degree, and finally used the operators to rank and select the alternatives [47].…”
Section: Multi-attribute Decision Making Methodsmentioning
confidence: 99%