scholarly journals Rough Best-Worst Method for Supplier Selection in Biofuel Companies based on Green criteria

2021 ◽  
Vol 4 (2) ◽  
pp. 1-12
Author(s):  
Navid Kazemitash ◽  
◽  
Hamed Fazlollahtabar ◽  
Mohammadmahdi Abbaspour ◽  
◽  
...  
Keyword(s):  
Information System ◽  
Set Theory ◽  
Rough Set ◽  
System Performance ◽  
Supplier Selection ◽  
Rough Set Theory ◽  
Supplier Selection Problem ◽  
Best Worst Method ◽  
Selection Of

This paper concerns with the integration of rough set theory with the Best Worst method to evaluate information system performance within supplier selection problem of biofuel companies. First, a set of main criteria and sub-criteria are collected and then to include uncertainty in decision making, rough set theory is employed. The rough best worst method is applied for weighing and supplier evaluation with respect to information system performance and environmental impacts. Further, a case study is conducted for biofuel company supplier selection and the results imply the effectiveness of the approach in tactical performance evaluation. The best criteria effective on the green supplier selection of ISs performance is determined to be Quality.

An approach to the analysis of design concepts using the rough set theory

2004 ◽  
Vol 18 (4) ◽  
pp. 343-355 ◽  
Author(s):  
D. ALISANTOSO ◽  
L.P. KHOO ◽  
I.B.H. LEE
Keyword(s):  
Information System ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Design Knowledge ◽  
Dynamic Design ◽  
Design Evolution ◽  
Design Concepts ◽  
Design Specifications

This paper describes an approach to the analysis of design concepts (DCs) using the rough set theory. The proposed approach attempts to extract design knowledge from past designs, and used the knowledge obtained to perform DC–capability mapping in a dynamic design evolution environment. The mapping enables designers to estimate the feasibility of a DC to meet stipulated design specifications. The proposed approach encompasses two algorithms, namely, the dissimilar objects algorithm and the attribute decomposition algorithm, to deal with an information system with unavailable information and multidecision attributes, respectively. The details of these algorithms are presented. A case study on the design of vacuum cleaners is used to illustrate the capability of the proposed approach.

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.

On Quasi Discrete Topological Spaces in Information Systems

2012 ◽  
Vol 3 (2) ◽  
pp. 38-52 ◽  
Author(s):  
Tutut Herawan
Keyword(s):  
Information System ◽  
Information Systems ◽  
Topological Space ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Topological Spaces ◽  
Discrete Topology

This paper presents an alternative way for constructing a topological space in an information system. Rough set theory for reasoning about data in information systems is used to construct the topology. Using the concept of an indiscernibility relation in rough set theory, it is shown that the topology constructed is a quasi-discrete topology. Furthermore, the dependency of attributes is applied for defining finer topology and further characterizing the roughness property of a set. Meanwhile, the notions of base and sub-base of the topology are applied to find attributes reduction and degree of rough membership, respectively.

Fuzzy Miner

2011 ◽  
pp. 299-321 ◽  
Author(s):  
Nikos Pelekis ◽  
Babis Theodoulidis ◽  
Ioannis Kopanakis ◽  
Yannis Theodoridis
Keyword(s):  
Data Mining ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Selection ◽  
Internet Routing ◽  
Data Mining Approach ◽  
New Information

QOSP Quality of Service Open Shortest Path First based on QoS routing has been recognized as a missing piece in the evolution of QoS-based services in the Internet. Data mining has emerged as a tool for data analysis, discovery of new information, and autonomous decision-making. This paper focuses on routing algorithms and their appli-cations for computing QoS routes in OSPF protocol. The proposed approach is based on a data mining approach using rough set theory, for which the attribute-value system about links of networks is created from network topology. Rough set theory offers a knowledge discovery approach to extracting routing-decisions from attribute set. The extracted rules can then be used to select significant routing-attributes and make routing-selections in routers. A case study is conducted to demonstrate that rough set theory is effective in finding the most significant attribute set. It is shown that the algorithm based on data mining and rough set offers a promising approach to the attribute-selection prob-lem in internet routing.

THE ALGORITHM ON KNOWLEDGE REDUCTION IN INCOMPLETE INFORMATION SYSTEMS

2002 ◽  
Vol 10 (01) ◽  
pp. 95-103 ◽  
Author(s):  
JIYE LIANG ◽  
ZONGBEN XU
Keyword(s):  
Information System ◽  
Information Systems ◽  
Incomplete Information ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Np Hard ◽  
Knowledge Reduction ◽  
Np Hard Problem ◽  
Incomplete Information Systems

Rough set theory is emerging as a powerful tool for reasoning about data, knowledge reduction is one of the important topics in the research on rough set theory. It has been proven that finding the minimal reduct of an information system is a NP-hard problem, so is finding the minimal reduct of an incomplete information system. Main reason of causing NP-hard is combination problem of attributes. In this paper, knowledge reduction is defined from the view of information, a heuristic algorithm based on rough entropy for knowledge reduction is proposed in incomplete information systems, the time complexity of this algorithm is O(|A|2|U|). An illustrative example is provided that shows the application potential of the algorithm.

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.

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