Fermatean fuzzy set extensions of SAW , ARAS , and VIKOR with applications in COVID ‐19 testing laboratory selection problem

An integrated method using intuitionistic fuzzy set and linear programming for supplier selection problem

IFAC Proceedings Volumes ◽

10.3182/20110828-6-it-1002.01591 ◽

2011 ◽

Vol 44 (1) ◽

pp. 6391-6395 ◽

Cited By ~ 2

Author(s):

M. Shahrokhi ◽

A. Bernard ◽

H. Shidpour

Keyword(s):

Linear Programming ◽

Fuzzy Set ◽

Supplier Selection ◽

Intuitionistic Fuzzy Set ◽

Selection Problem ◽

Integrated Method ◽

Intuitionistic Fuzzy ◽

Supplier Selection Problem

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Hesitant Fuzzy SWARA-Complex Proportional Assessment Approach for Sustainable Supplier Selection (HF-SWARA-COPRAS)

Symmetry ◽

10.3390/sym12071152 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1152

Author(s):

Pratibha Rani ◽

Arunodaya Raj Mishra ◽

Raghunathan Krishankumar ◽

Abbas Mardani ◽

Fausto Cavallaro ◽

...

Keyword(s):

Fuzzy Set ◽

Supplier Selection ◽

Assessment Method ◽

Selection Problem ◽

Assessment Process ◽

Hesitant Fuzzy Set ◽

Uncertain Information ◽

Sustainable Supply Chain ◽

Sustainable Supplier Selection ◽

Supplier Selection Problem

The selection of sustainable supplier is an extremely important for sustainable supply chain management (SSCM). The assessment process of sustainable supplier selection is a complicated task for decision experts due to involvement of several qualitative and quantitative criteria. As the uncertainty is commonly occurred in sustainable supplier selection problem and hesitant fuzzy set (HFS), an improvement of Fuzzy Set (FS), has been proved as one of the efficient and superior ways to express the uncertain information arisen in practical problems. The present study proposes a novel framework based on COPRAS (Complex Proportional Assessment) method and SWARA (Step-wise Weight Assessment Ratio Analysis) approach to evaluate and select the desirable sustainable supplier within the HFSs context. In the proposed method, an extended SWARA method is employed for determining the criteria weights based on experts’ preferences. Next, to illustrate the efficiency and practicability of the proposed methodology, an empirical case study of sustainable supplier selection problem is taken under Hesitant Fuzzy (HF) environment. Further, sensitivity analysis is performed to check the stability of the presented methodology. At last, a comparison with existing methods is conducted to verify the strength of the obtained result. The final outcomes confirm that the developed framework is more consistent and powerful than other existing approaches.

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Is Psychology a Science or a Fuzzy Set?

Contemporary Psychology ◽

10.1037/017151 ◽

1978 ◽

Vol 23 (5) ◽

pp. 319-320

Author(s):

LEWIS WOLFGANG BRANDT

Keyword(s):

Fuzzy Set

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Methodology of ECG Interpretation in the Padova Program

Methods of Information in Medicine ◽

10.1055/s-0038-1634804 ◽

1990 ◽

Vol 29 (04) ◽

pp. 386-392 ◽

Cited By ~ 12

Author(s):

R. Degani ◽

G. Bortolan

Keyword(s):

Decision Making ◽

Medical School ◽

Fuzzy Set ◽

Medical Knowledge ◽

Main Aspect ◽

Measurement Evaluation ◽

Possibility Distributions ◽

Linguistic Decision Making ◽

The University ◽

Ecg Interpretation

AbstractThe main lines ofthe program designed for the interpretation of ECGs, developed in Padova by LADSEB-CNR with the cooperation of the Medical School of the University of Padova are described. In particular, the strategies used for (i) morphology recognition, (ii) measurement evaluation, and (iii) linguistic decision making are illustrated. The main aspect which discerns this program in comparison with other approaches to computerized electrocardiography is its ability of managing the imprecision in both the measurements and the medical knowledge through the use of fuzzy-set methodologies. So-called possibility distributions are used to represent ill-defined parameters as well as threshold limits for diagnostic criteria. In this way, smooth conclusions are derived when the evidence does not support a crisp decision. The influence of the CSE project on the evolution of the Padova program is illustrated.

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