Selection of Suppliers Based on Rough Set Theory and Fuzzy TOPSIS Algorithm

2008 ◽  
Author(s):  
Zhiping Fan ◽  
Tiansheng Hong ◽  
Zhizhuang Liu
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Fuzzy Topsis ◽  
Selection Of

scholarly journals Application of machine learning and rough set theory in lean maintenance decision support system development

2021 ◽  
Vol 23 (4) ◽  
pp. 695-708
Author(s):  
Katarzyna Antosz ◽  
Małgorzata Jasiulewicz-Kaczmarek ◽  
Łukasz Paśko ◽  
Chao Zhang ◽  
Shaoping Wang
Keyword(s):  
Machine Learning ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
System Development ◽  
Decision Makers ◽  
Manufacturing Companies ◽  
New Approach ◽  
Structured Approach ◽  
Selection Of

Lean maintenance concept is crucial to increase the reliability and availability of maintenance equipment in the manufacturing companies. Due the elimination of losses in maintenance processes this concept reduce the number of unplanned downtime and unexpected failures, simultaneously influence a company’s operational and economic performance. Despite the widespread use of lean maintenance, there is no structured approach to support the choice of methods and tools used for the maintenance function improvement. Therefore, in this paper by using machine learning methods and rough set theory a new approach was proposed. This approach supports the decision makers in the selection of methods and tools for the effective implementation of Lean Maintenance.

scholarly journals Methodology for the Construction of a Rule-Based Knowledge Base Enabling the Selection of Appropriate Bronze Heat Treatment Parameters Using Rough Sets

2015 ◽  
Vol 60 (1) ◽  
pp. 309-312 ◽  
Author(s):  
Z. Górny ◽  
S. Kluska-Nawarecka ◽  
D. Wilk-Kołodziejczyk ◽  
K. Regulski
Keyword(s):  
Heat Treatment ◽  
Knowledge Base ◽  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Rough Set Theory ◽  
Exploratory Research ◽  
Rule Based ◽  
The Creation ◽  
Selection Of

Abstract Decisions regarding appropriate methods for the heat treatment of bronzes affect the final properties obtained in these materials. This study gives an example of the construction of a knowledge base with application of the rough set theory. Using relevant inference mechanisms, knowledge stored in the rule-based database allows the selection of appropriate heat treatment parameters to achieve the required properties of bronze. The paper presents the methodology and the results of exploratory research. It also discloses the methodology used in the creation of a knowledge base.

The Application of Fuzzy Theory and Gray-Based Rough Set Theory in the Supplier Selection Decision Making

2010 ◽  
Vol 26-28 ◽  
pp. 559-563 ◽  
Author(s):  
Kai Jun Leng ◽  
Shu Hong Zhang
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Supplier Selection ◽  
Rough Set Theory ◽  
Fuzzy Theory ◽  
Decision Makers ◽  
Location Selection ◽  
Integrated Method ◽  
Selection Decision ◽  
Selection Of

This work presents the combination of fuzzy theory and rough set theory to solve facility location selection problems under the condition of involving different objective/subjective attributes. We try to utilize individual merits for each method and combine it to form a reliable selection of alternative suppliers. An empirical example is illustrated to show the effectiveness of the integrated method. Our results showed that the integrated method can allow decision makers to get the best candidate of supplier location, and is recommended in the practice therefore.

scholarly journals Rough Set Theory Based Fuzzy TOPSIS on Serious Game Design Evaluation Framework

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Chung-Ho Su ◽  
Ken T.-K. Chen ◽  
Kuo-Kuang Fan
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Game Design ◽  
Rough Set Theory ◽  
Evaluation Model ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Evaluation Framework ◽  
Design Evaluation ◽  
Fuzzy Delphi

This study presents a hybrid methodology for solving the serious game design evaluation in which evaluation criteria are based on meaningful learning, ARCS motivation, cognitive load, and flow theory (MACF) by rough set theory (RST) and experts’ selection. The purpose of this study tends to develop an evaluation model with RST based fuzzy Delphi-AHP-TOPSIS for MACF characteristics. Fuzzy Delphi method is utilized for selecting the evaluation criteria, Fuzzy AHP is used for analyzing the criteria structure and determining the evaluation weight of criteria, and Fuzzy TOPSIS is applied to determine the sequence of the evaluations. A real case is also used for evaluating the selection of MACF criteria design for four serious games, and both the practice and evaluation of the case could be explained. The results show that the playfulness (C24), skills (C22), attention (C11), and personalized (C35) are determined as the four most important criteria in the MACF selection process. And evaluation results of case study point out that Game 1 has the best score overall (Game 1 > Game 3 > Game 2 > Game 4). Finally, proposed evaluation framework tends to evaluate the effectiveness and the feasibility of the evaluation model and provide design criteria for relevant multimedia game design educators.

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