Heronian Mean Operators Based on Novel Complex Linear Diophantine Uncertain Linguistic Variables and Their Applications in Multi-Attribute Decision Making
Abstract
:1. Introduction
- For , based on the well-known characteristic of CIFSs, we obtained , the principle of CIFS has been neglected. For this, the CLDULS is massive suitable to determine the solution of the above problem based on reference parameters , then . The principle of CLDULS is suitable for every kind of dilemmas.
- For , based on the well-known characteristic of CPFSs, we obtained , the principle of CPFS has been neglected. For this, the CLDULS is massive suitable to determine the solution of the above problem based on reference parameters , then . The principle of CLDULS is suitable for every kind of dilemmas.
- For , based on the well-known characteristic of CQROFSs, we obtained , the principle of CQROFS has been neglected. For this, the CLDULS is massive suitable to determine the solution of the above problem based on reference parameters , then . The principle of CLDULS is suitable for every kind of dilemmas.
- To elaborate the CLDULS and fostered their functional laws.
- To investigate the Einstein functional laws and their connected tasks, for example, score and exactness esteems.
- To use the force Einstein collection administrators dependent on CLDULS and discussed their extraordinary cases.
- To foster a MADM procedure by utilizing the explained administrators with CLDULNs to discover consistency and validness of the expounded approaches.
- To discover the incomparability and consistency of the explained administrators with the assistance of similar investigation and their graphical articulations.
2. Preliminaries
- When ;
- When ;
- When
- When ;
- When ;
- When .
3. Complex Linear Diophantine Uncertain Linguistic Sets
- When ;
- When ;
- When
- When ;
- When ;
- When .
- ;
- ;
- ;
- ;
- ;
- .
4. Complex Linear Diophantine Uncertain Linguistic Power Einstein Aggregation Operators
5. MADM Technique Based on Elaborated Operators
- Step 1: By using the complex linear Diophantine uncertain linguistic information, we develop the decision matrix, such that
- Step 2: To aggregate the developed decision matrix, we use the CLDULPEA, CLDULPEWA, CLDULPEG and CLDULPEWG operators.
- Step 3: To determine the score values of the aggregated values, we use the score function.
- Step 4: By using the score values, we rank to all alternatives is to examine the best optimal from the group of alternatives.
- : Produce a development adjusted to the incredible organizations.
- : Produce a development adjusted to the mid-level organizations.
- : Produce a development adjusted to the Low-level organizations.
- : Produce a development adjusted to all organizations.
- : Beneficial in the Influential circumstances.
- : Beneficial in the mid circumstances.
- : Beneficial in the long circumstances.
- : Cost of the production plan.
Comparative Analysis
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
ULS | Uncertain linguistic sets |
CFS | Complex fuzzy sets |
LDFS | Linear Diophantine fuzzy sets |
PE | Power Einstein |
CLDULS | Complex linear Diophantine uncertain linguistic sets |
CLDULPEA | Complex linear Diophantine uncertain linguistic power Einstein averaging |
CLDULPEWA | Complex linear Diophantine uncertain linguistic power Einstein weighted averaging |
CLDULPEG | Complex linear Diophantine uncertain linguistic power Einstein geometric |
CLDULPEWG | Complex linear Diophantine uncertain linguistic power Einstein weighted geometric |
FS | Fuzzy sets |
IFS | Intuitionistic fuzzy sets |
CIFS | Complex intuitionistic fuzzy sets |
PFS | Pythagorean fuzzy sets |
CPFS | Complex Pythagorean fuzzy sets |
QROFS | q-rung orthopair fuzzy sets |
CQROFS | Complex q-rung orthopair fuzzy sets |
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Symbols | Meanings | Symbols | Meanings | Symbols | Meanings |
---|---|---|---|---|---|
Universal set | Truth grade | Real part of truth grade | |||
Element of universal set | Falsity grade | Imaginary part of truth grade | |||
Reference parameter for truth grade | Reference parameter for falsity grade | Uncertain linguistic terms |
Methods | Score Values | Ranking Values |
---|---|---|
Riaz and Hashmi [20] | Cannot be Calculated | Cannot be Calculated |
Ali and Mahmood [36] | Cannot be Calculated | Cannot be Calculated |
CLDULPEA operator | ||
CLDULPEWA operator | ||
CLDULPEG operator | ||
CLDULPEWG operator |
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Ali, Z.; Mahmood, T.; Santos-García, G. Heronian Mean Operators Based on Novel Complex Linear Diophantine Uncertain Linguistic Variables and Their Applications in Multi-Attribute Decision Making. Mathematics 2021, 9, 2730. https://doi.org/10.3390/math9212730
Ali Z, Mahmood T, Santos-García G. Heronian Mean Operators Based on Novel Complex Linear Diophantine Uncertain Linguistic Variables and Their Applications in Multi-Attribute Decision Making. Mathematics. 2021; 9(21):2730. https://doi.org/10.3390/math9212730
Chicago/Turabian StyleAli, Zeeshan, Tahir Mahmood, and Gustavo Santos-García. 2021. "Heronian Mean Operators Based on Novel Complex Linear Diophantine Uncertain Linguistic Variables and Their Applications in Multi-Attribute Decision Making" Mathematics 9, no. 21: 2730. https://doi.org/10.3390/math9212730
APA StyleAli, Z., Mahmood, T., & Santos-García, G. (2021). Heronian Mean Operators Based on Novel Complex Linear Diophantine Uncertain Linguistic Variables and Their Applications in Multi-Attribute Decision Making. Mathematics, 9(21), 2730. https://doi.org/10.3390/math9212730