Application of Intuitionistic Fuzzy Entropy to Disruption Risk Management in Aerospace Supply Chain

2016 ◽  
Vol 10 (3) ◽  
pp. 1035-1046 ◽  
Author(s):  
Kuo-Hwa Chang ◽  
Chao-Ran Cheng
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Fuzzy Entropy ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Disruption Risk

Multi-Criteria Decision-Making Model using Intuitionistic Fuzzy Entropy and Variable Weight Theory

Mekatronika ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 18-25
Author(s):  
Omar Ayasrah ◽  
Faiz Mohd Turan
Keyword(s):  
Decision Making ◽  
Fuzzy Entropy ◽  
Decision Makers ◽  
Entropy Measure ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Variable Weight ◽  
Intuitionistic Fuzzy Entropy ◽  
Perform Sensitivity Analysis ◽  
Almost All

The aim of this research is to develop a new multi-criteria decision-making method that integrates an intuitionistic fuzzy entropy measure and variable weight theory to be implemented in different fields to provide a solution for MCDM problems when the available information is incomplete. A limited number of studies have considered determining decision maker’s weights by performing objective techniques, and almost all of these researches detected a constant weights for the decision makers. In addition, most of the MCDM studies were not formulated to perform sensitivity analysis. The new method is based on the TOPSIS model with an intuitionistic fuzzy entropy measure in the exponential-related function form and the engagement of the variable weight theory to determine weights for the decision-makers that vary as per attibutes. Lastly, a mathematical model was developed in this research to be as an input for developing the mobile-aplication based method in future for virtual use of the new MCDM method.

Kernel intuitionistic fuzzy entropy clustering for MRI image segmentation

2019 ◽  
Vol 24 (6) ◽  
pp. 4003-4026 ◽  
Author(s):  
Dhirendra Kumar ◽  
R. K. Agrawal ◽  
Hanuman Verma
Keyword(s):  
Image Segmentation ◽  
Fuzzy Entropy ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Mri Image

Modeling Disruption Risk in Supply Chain Risk Management

2012 ◽  
Vol 3 (3) ◽  
pp. 15-39 ◽  
Author(s):  
Ragip Ufuk Bilsel ◽  
A. Ravi Ravindran
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Individual Component ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Numerical Examples ◽  
Disruption Risk ◽  
The Individual ◽  
Disruption Risks ◽  
Analytical Frameworks

Disruptions have often been ignored in supply chain models due to their infrequency; however, there is evidence that disruptions are among the most significant threats to supply chains. This paper presents analytical methods to model and quantify disruption risks. The methods consist of breaking disruption risks down into four components: impact, occurrence, detectability and recovery. Analytical frameworks to quantify each individual component is provided. Methods to combine the individual components of risk are discussed and illustrated with numerical examples.

scholarly journals Intuitionistic Fuzzy Entropy for Group Decision Making of Water Engineering Project Delivery System Selection

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1101 ◽  
Author(s):  
Liu ◽  
Qian ◽  
Lin ◽  
Zhang ◽  
Zhu
Keyword(s):  
Delivery System ◽  
Group Decision ◽  
Weighted Average ◽  
Fuzzy Entropy ◽  
Project Delivery ◽  
Delivery Mode ◽  
Practical Case ◽  
Engineering Project ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy

The project delivery mode is an extremely important link in the life cycle of water engineering. Many cases show that increases in the costs, construction period, and claims in the course of the implementation of water engineering are related to the decision of the project delivery mode in the early stages. Therefore, it is particularly important to choose a delivery mode that matches the water engineering. On the basis of identifying the key factors that affect the decision on the project delivery system and establishing a set of index systems, a comprehensive decision of engineering transaction is essentially considered to be a fuzzy multi-attribute group decision. In this study, intuitionistic fuzzy entropy was used to determine the weight of the influencing factors on the engineering transaction mode; then, intuitionistic fuzzy entropy was used to determine the weight of decision experts. Thus, a comprehensive scheme-ranking model based on an intuitionistic fuzzy hybrid average (IFHA) operator and intuitionistic fuzzy weighted average (IFWA) operator was established. Finally, a practical case analysis of a hydropower station further demonstrated the feasibility, objectivity, and scientific nature of the decision model.

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