Fermatean fuzzy sets and their variants
Amal Kumar Adak; Manish Kumar Gunjan
Abstract
Stock portfolio problems are one of the most relevant real-world problems. In this study, we discuss the portfolio's risk amount, rate of risk-return, and expected return rate under a Fermatean fuzzy environment. A linear programming problem is used to formulate a Fermatean fuzzy portfolio. The Fermatean ...
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Stock portfolio problems are one of the most relevant real-world problems. In this study, we discuss the portfolio's risk amount, rate of risk-return, and expected return rate under a Fermatean fuzzy environment. A linear programming problem is used to formulate a Fermatean fuzzy portfolio. The Fermatean fuzzy portfolio is converted to a deterministic form using the score function. Lingo software is used to solve these deterministic portfolio problems. The main feature of this model is that investors can select a risk coefficient to enhance predicted returns and customize their strategies according to their circumstances. An example is offered that illustrates the effectiveness and dependability of the proposed approach.
Picture fuzzy sets and their variants
Amal Kumar Adak; Manish Kumar Gunjan; Niwan Kumar Agarwal
Abstract
Picture Fuzzy Sets (PFSs) are expanded to include Intuitionistic Fuzzy Sets (IFSs), with the extra advantage of avoiding underlying limitations. PFS based models may be adequate in situations when we face opinions involving more answer of types: yes, abstain and no. In this paper, the concepts of semi-prime ...
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Picture Fuzzy Sets (PFSs) are expanded to include Intuitionistic Fuzzy Sets (IFSs), with the extra advantage of avoiding underlying limitations. PFS based models may be adequate in situations when we face opinions involving more answer of types: yes, abstain and no. In this paper, the concepts of semi-prime ideals of PFS are explained. We also discussed how to construct picture fuzzy regular and intra-regular ideals and represents certain fundamental facts.
Pythagorean fuzzy sets and their variants
Amal Kumar Adak; Gaurikant Kumar
Abstract
Multiple Criteria Decision Analysis (MCDA) has been widely investigated and successfully applied to many fields,owing to its great capability of modeling the process of actual decision-making problems and establishing proper evaluation and assessment mechanisms. With the development of management and ...
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Multiple Criteria Decision Analysis (MCDA) has been widely investigated and successfully applied to many fields,owing to its great capability of modeling the process of actual decision-making problems and establishing proper evaluation and assessment mechanisms. With the development of management and economics, real-world decision-making problem are becoming diversified and complicated to an increasing extent, especially within a changeable and unpredictable enviroment. Multi-criteria is a decision-making technique that explicitly evaluates numerous contradictory criteria. TOPSIS is a well-known multi-criteria decision-making process. The goal of this research is to use TOPSIS to solve MCDM problems in a Pythagorean fuzzy environment. The distance between two Pythagorean fuzzy numbers is utilized to create the model using the spherical distance measure. To construct a ranking order of alternatives and determine the best one,the revised index approach is utilized. Finally, we look at a set of MCDM problems to show how the proposed method and approach work in practice. In addition, it shows comparative data from the relative closeness and updated index methods.
