New Interval-Valued Intuitionistic Fuzzy Behavioral MADM Method and Its Application in the Selection of Photovoltaic Cells

In this article, it is pointed out that the existing intuitionistic fuzzy and T-spherical fuzzy Einstein averaging and geometric operators have some limitations. To overcome these limitations, we proposed some new averaging and geometric operators in the T-spherical fuzzy environment instead of the intuitionistic fuzzy environment because the T-spherical fuzzy set is the most generalized form and the proposed operators can be particularized to the intuitionistic fuzzy environment. First, new operational laws for T-spherical fuzzy information are defined, on the basis of which Einstein geometric interaction operators and Einstein averaging interactive aggregation operators are then proposed. Some basic properties and advantages of proposed aggregation operators are also discussed. Moreover, the proposed operators are applied to the MADM problem to check their reliability. The superiority of the proposed operators over existing work is checked with the help of an example.

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A NEW DECISION MODEL FOR CROSS-DOCKING CENTER LOCATION IN LOGISTICS NETWORKS UNDER INTERVAL-VALUED INTUITIONISTIC FUZZY UNCERTAINTY

Transport ◽

10.3846/transport.2019.7442 ◽

2019 ◽

Vol 34 (1) ◽

pp. 30-40 ◽

Cited By ~ 7

Author(s):

Seyed Meysam Mousavi ◽

Jurgita Antuchevičienė ◽

Edmundas Kazimieras Zavadskas ◽

Behnam Vahdani ◽

Hassan Hashemi

Keyword(s):

Distribution Networks ◽

Decision Matrix ◽

Uncertainty Interval ◽

Location Selection ◽

Intuitionistic Fuzzy ◽

Logistics Networks ◽

Weighted Arithmetic ◽

Cross Docking ◽

Interval Valued ◽

Selection Of

Cross-dock has been a novel logistic approach to effectively consolidate and distribute multiple products in logistics networks. Location selection of cross-docking centers is a decision problem under different conflicting criteria. The decision has a vital part in the strategic design of distribution networks in logistics management. Conventional methods for the location selection of cross-docking centers are insufficient for handling uncertainties in Decision-Makers (DMs) or experts’ opinions. This study presents a modern Multi-Criteria Group Decision-Making (MCGDM) model, which applies the concept of compromise solution under uncertainty. To address uncertainty, Interval-Valued Intuitionistic Fuzzy (IVIF) sets are used. In this paper, first an IVIF-weighted arithmetic averaging (IVIF-WAA) operator is used in order to aggregate all IVIF-decision matrices, which were made by a team of the DMs into final IVIF-decision matrix. Then, a new Collective Index (CI) is developed that simultaneously regards distances of cross-docking centers as candidates from the IVIF-ideal points. Finally, the feasibility and practicability of proposed MCGDM model is illustrated with an application example on location choices of cross-docking centers to the logistics network design.

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Cybersecurity against the Loopholes in Industrial Control Systems Using Interval-Valued Complex Intuitionistic Fuzzy Relations

Applied Sciences ◽

10.3390/app11167668 ◽

2021 ◽

Vol 11 (16) ◽

pp. 7668 ◽

Cited By ~ 1

Author(s):

Abdul Nasir ◽

Naeem Jan ◽

Abdu Gumaei ◽

Sami Ullah Khan ◽

Fahad R. Albogamy

Keyword(s):

Hasse Diagram ◽

Fuzzy Relations ◽

Industrial Control ◽

Industrial Control Systems ◽

Hasse Diagrams ◽

Intuitionistic Fuzzy ◽

The Many ◽

First Time ◽

Interval Valued ◽

Selection Of

Technology is rapidly advancing and every aspect of life is being digitalized. Since technology has made life much better and easier, so organizations, such as businesses, industries, companies and educational institutes, etc., are using it. Despite the many benefits of technology, several risks and serious threats, called cyberattacks, are associated with it. The method of neutralizing these cyberattacks is known as cybersecurity. Sometimes, there are uncertainties in recognizing a cyberattack and nullifying its effects using righteous cybersecurity. For that reason, this article introduces interval-valued complex intuitionistic fuzzy relations (IVCIFRs). For the first time in the theory of fuzzy sets, we investigated the relationships among different types of cybersecurity and the sources of cyberattacks. Moreover, the Hasse diagram for the interval-valued complex intuitionistic partial order set and relation is defined. The concepts of the Hasse diagram are used to inspect different cybersecurity techniques and practices. Then, using the properties of Hasse diagrams, the most beneficial technique is identified. Furthermore, the best possible selection of types of cybersecurity is made after putting some restrictions on the selection. Lastly, the advantages of the proposed methods are illuminated through comparison tests.

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An Extension of the CODAS Approach Using Interval-Valued Intuitionistic Fuzzy Set for Sustainable Material Selection in Construction Projects with Incomplete Weight Information

Symmetry ◽

10.3390/sym11030393 ◽

2019 ◽

Vol 11 (3) ◽

pp. 393 ◽

Cited By ~ 13

Author(s):

Jagannath Roy ◽

Sujit Das ◽

Samarjit Kar ◽

Dragan Pamučar

Keyword(s):

Construction Projects ◽

Material Selection ◽

Optimal Selection ◽

Bottom Line ◽

Significant Group ◽

Intuitionistic Fuzzy ◽

Incomplete Weight ◽

Incomplete Weight Information ◽

Interval Valued ◽

Selection Of

Optimal selection of sustainable materials in construction projects can benefit several stakeholders in their respective industries with the triple bottom line (TBL) framework in a broader perspective of greater business value. Multiple criteria of social, environmental, and economic aspects should be essentially accounted for the optimal selection of materials involving the significant group of experts to avoid project failures. This paper proposes an evaluation framework for solving multi criteria decision making (MCDM) problems with incomplete weight information by extending the combinative distance assessment (CODAS) method with interval-valued intuitionistic fuzzy numbers. To compute the unknown weights of the evaluation criteria, this paper presents an optimization model based on the interval-valued intuitionistic fuzzy distance measure. In this study, we emphasize the importance of individual decision makers. To illustrate the proposed approach, an example of material selection in automotive parts industry is presented followed by a real case study of brick selection in sustainable building construction projects. The comparative study indicates the advantages of the proposed approach in comparison with the some relevant approaches. A sensitivity analysis of the proposed IVIF-CODAS method has been performed by changing the criteria weights, where the results show a high degree of stability.

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AN APPROACH TO THE PRODUCTION PLANT LOCATION SELECTION BASED ON THE USE OF THE ATANASSOV INTERVAL-VALUED INTUITIONISTIC FUZZY SETS

Transport ◽

10.3846/16484142.2017.1321041 ◽

2018 ◽

Vol 33 (3) ◽

pp. 835-842 ◽

Cited By ~ 4

Author(s):

Dragiša STANUJKIĆ ◽

Ieva MEIDUTĖ-KAVALIAUSKIENĖ

Keyword(s):

Manufacturing Industry ◽

Fuzzy Numbers ◽

Real Problem ◽

Production Plant ◽

Plant Selection ◽

Location Selection ◽

Intuitionistic Fuzzy Numbers ◽

Intuitionistic Fuzzy ◽

Interval Valued ◽

Selection Of

Location planning is one of very important tasks in the manufacturing industry. There are various factors that influence the selection of a location of a production plant. In cases of selection, when uncertainty and a need for predicting are significantly manifested, the use of fuzzy or grey numbers can be very useful. That is why an approach based on the use of Interval-Valued Intuitionistic Fuzzy Numbers (IVIFNs) for the selection of the most appropriate location of a production plant is considered in this article. The efficiency of the proposed approach is considered on an example, based on the real problem of the smelter and refinery production plant selection.

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