Hesitant fuzzy sets and their variants
Lubna Shafi; Shilpi Jain; Praveen Agarwal; Pervaiz Iqbal; Aadil Rashid Sheergojri
Abstract
Fuzzy time series forecasting is an approach for dealing with uncertainty in time series data that uses fuzzy logic. The hesitant fuzzy set theory emphasizes the chances of capturing fuzziness and uncertainty due to randomness better than the classic fuzzy set theory. This study aims to improve the previously ...
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Fuzzy time series forecasting is an approach for dealing with uncertainty in time series data that uses fuzzy logic. The hesitant fuzzy set theory emphasizes the chances of capturing fuzziness and uncertainty due to randomness better than the classic fuzzy set theory. This study aims to improve the previously identified hesitant fuzzy time series forecasting models by including various degrees of hesitation to improve forecasting performance. The goal is to deal with the issue of identifying a common membership grade when several fuzzification methods are available to fuzzify time series data.The proposed method utilizes trapezoidal and bell-shaped fuzzy membership functions for constructing hesitant fuzzy sets.Ahesitant fuzzy weighted averaging operator is then applied to the hesitant fuzzy elements to create fuzzy logical relations.The suggested technique is employed to forecast enrollment in the University of Alabama and cancer incidence rates in India. The efficiency of the proposed forecasting approach is determined by rigorously comparing it to various computational fuzzy time series forecasting methods in terms of error measurements like root mean square error, average forecasting error, and mean absolute deviation. The validity of the proposed forecasting model is verified by using correlation coefficients, coefficients of determination, tracking signals, and performance parameters. The significance of improved accuracy in forecasted results is confirmed as well using the two-tailed t-test. The results of the study revealed that the enhanced hesitant fuzzy time series model is more effective and accurate in forecasting the university enrolment of Alabama and the cancer incidence rates of India.
Hesitant fuzzy sets and their variants
Madineh Farnam; Majid Darehmiraki
Abstract
Complex nature of the current market is often caused by uncertainties, data uncertainties, their manner of use, and differences in managers' viewpoints. To overcome these problems, Hesitant Fuzzy Sets (HFSs) can be useful as the extension of fuzzy set theory, in which the degree of membership of an element ...
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Complex nature of the current market is often caused by uncertainties, data uncertainties, their manner of use, and differences in managers' viewpoints. To overcome these problems, Hesitant Fuzzy Sets (HFSs) can be useful as the extension of fuzzy set theory, in which the degree of membership of an element can be a set of possible values and provide greater flexibility in design and, thus, model performance. The power of this application becomes clear when different decision-makers tend to independently record their views. In most real-world situations, there are several goals for managers to achieve the desired performance. Therefore, in this study, a description of the solution of the Hesitant Fuzzy Linear Programming (HFLP) problem for solving hesitant fuzzy multi-objective problems is considered. In the following, the multi-objective and three-level supply chain management problem is modeled with the hesitant fuzzy approach. Then, with an example, the flexibility of the model responses is evaluated by the proposed method. The hesitant fuzzy model presented in this study can be extended to other supply chain management problems.
Hesitant fuzzy sets and their variants
Madineh Farnam; Majid Darehmiraki
Abstract
For the three last decades, the multi-objective fractional programming problem has attracted the attention of many researchers due to various applications in production planning, financial field, and inventory management, and so on. The main aim of this study is to introduce a new application of hesitant ...
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For the three last decades, the multi-objective fractional programming problem has attracted the attention of many researchers due to various applications in production planning, financial field, and inventory management, and so on. The main aim of this study is to introduce a new application of hesitant fuzzy sets in real-life modeling. We intend to model multi-objective linear fractional programming problems under a hesitant fuzzy environment and present a procedure to solve them. the increasing applications of multi-objective linear fractional programming problems and the lack of research papers in this field under a hesitant fuzzy environment are the main motivations of this study. In a hesitant fuzzy set, the membership degree of an element belongs to the set can be represented by several possible values in [0,1]. These values can be chosen by different experts that cannot reach a single opinion in determining a membership degree. so, in our model several evaluations for each of goals established by decision makers based on their attitudes. The generalization of the fuzzy decision-making principle and some new concepts provide an effective solution procedure for the problem. Finally, a practical example is extended to illustrate the applicability of the proposed method.
