Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making Problems
The fundamental notions of the intuitionistic hesitant fuzzy set (IHFS) and rough set (RS) are general mathematical tools that may easily manage imprecise and uncertain information. The EDAS (Evaluation based on Distance from Average Solution) approach has an important role in decision-making (DM) p...
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2024-12-01
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| author | Muhammad Kamraz Khan Muhammad Sajjad Ali Khan Kamran Ioan-Lucian Popa |
| author_facet | Muhammad Kamraz Khan Muhammad Sajjad Ali Khan Kamran Ioan-Lucian Popa |
| author_sort | Muhammad Kamraz Khan |
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| description | The fundamental notions of the intuitionistic hesitant fuzzy set (IHFS) and rough set (RS) are general mathematical tools that may easily manage imprecise and uncertain information. The EDAS (Evaluation based on Distance from Average Solution) approach has an important role in decision-making (DM) problems, particularly in multi-attribute group decision-making (MAGDM) scenarios, where there are many conflicting criteria. This paper aims to introduce the IHFR-EDAS approach, which utilizes the IHF rough averaging aggregation operator. The aggregation operator is crucial for aggregating intuitionistic hesitant fuzzy numbers into a cohesive component. Additionally, we introduce the concepts of the IHF rough weighted averaging (IHFRWA) operator. For the proposed operator, a new accuracy function (AF) and score function (SF) are established. Subsequently, the suggested approach is used to show the IHFR-EDAS model for MAGDM and its stepwise procedure. In conclusion, a numerical example of the constructed model is demonstrated, and a general comparison between the investigated models and the current methods demonstrates that the investigated models are more feasible and efficient than the present methods. |
| format | Article |
| id | doaj-art-acf8323921fb45e79c55617807bedc5e |
| institution | Kabale University |
| issn | 2075-1680 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Axioms |
| spelling | doaj-art-acf8323921fb45e79c55617807bedc5e2025-01-24T13:22:10ZengMDPI AGAxioms2075-16802024-12-011412110.3390/axioms14010021Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making ProblemsMuhammad Kamraz Khan0Muhammad Sajjad Ali Khan1Kamran2Ioan-Lucian Popa3Department of Mathematics, Islamia College Peshawar, Peshawar 25120, Khyber Pakhtoonkhwa, PakistanDepartment of Mathematics, Khushal Khan Khattak University, Karak 27200, Khyber Pakhtunkhwa, PakistanDepartment of Mathematics, Islamia College Peshawar, Peshawar 25120, Khyber Pakhtoonkhwa, PakistanDepartment of Computing, Mathematics and Electronics, “1 Decembrie 1918” University of Alba Iulia, 510009 Alba Iulia, RomaniaThe fundamental notions of the intuitionistic hesitant fuzzy set (IHFS) and rough set (RS) are general mathematical tools that may easily manage imprecise and uncertain information. The EDAS (Evaluation based on Distance from Average Solution) approach has an important role in decision-making (DM) problems, particularly in multi-attribute group decision-making (MAGDM) scenarios, where there are many conflicting criteria. This paper aims to introduce the IHFR-EDAS approach, which utilizes the IHF rough averaging aggregation operator. The aggregation operator is crucial for aggregating intuitionistic hesitant fuzzy numbers into a cohesive component. Additionally, we introduce the concepts of the IHF rough weighted averaging (IHFRWA) operator. For the proposed operator, a new accuracy function (AF) and score function (SF) are established. Subsequently, the suggested approach is used to show the IHFR-EDAS model for MAGDM and its stepwise procedure. In conclusion, a numerical example of the constructed model is demonstrated, and a general comparison between the investigated models and the current methods demonstrates that the investigated models are more feasible and efficient than the present methods.https://www.mdpi.com/2075-1680/14/1/21intuitionistic hesitant fuzzy setrough setweighted averaging operatorEDAS approachMAGDM |
| spellingShingle | Muhammad Kamraz Khan Muhammad Sajjad Ali Khan Kamran Ioan-Lucian Popa Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making Problems Axioms intuitionistic hesitant fuzzy set rough set weighted averaging operator EDAS approach MAGDM |
| title | Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making Problems |
| title_full | Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making Problems |
| title_fullStr | Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making Problems |
| title_full_unstemmed | Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making Problems |
| title_short | Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making Problems |
| title_sort | intuitionistic hesitant fuzzy rough aggregation operator based edas method and its application to multi criteria decision making problems |
| topic | intuitionistic hesitant fuzzy set rough set weighted averaging operator EDAS approach MAGDM |
| url | https://www.mdpi.com/2075-1680/14/1/21 |
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