Exponential operations and aggregation operators of interval neutrosophic sets and their decision making methods
1Department of Electrical and Information Engineering, Shaoxing University, 508 Huancheng West Road, Shaoxing, 312000 Zhejiang Province People's Republic of China.
Springerplus
|December 27, 2016
Summary
This study introduces new exponential operational laws for interval neutrosophic sets (INSs) using interval neutrosophic numbers (INNs) as exponents. These advancements enable novel decision-making methods for complex problems like global supplier selection.
Area of Science:
- Decision Sciences
- Fuzzy Set Theory
- Operations Research
Background:
- Interval neutrosophic sets (INSs) generalize existing fuzzy set theories.
- Current INS operational laws use crisp exponents, limiting decision-making flexibility.
- A need exists for advanced INS operational laws accommodating uncertain parameters.
Purpose of the Study:
- To introduce novel exponential operational laws for INSs with interval neutrosophic number (INN) exponents.
- To develop interval neutrosophic weighted exponential aggregation (INWEA) and dual (DINWEA) operators.
- To propose decision-making methods utilizing these new operators and cosine measure functions.
Main Methods:
- Development of new exponential operational laws for INSs with INN bases and exponents.
- Formulation of INWEA and DINWEA aggregation operators.
- Application of cosine measure functions for comparing INNs and dual INNs.
- Construction of decision-making frameworks based on the proposed operators.
Main Results:
- Successfully introduced novel exponential operational laws for INSs.
- Developed INWEA and DINWEA operators capable of handling interval neutrosophic uncertainty.
- Demonstrated the effectiveness of the proposed methods through a global supplier selection case study.
- Validated the applicability and rationality of the decision-making approach.
Conclusions:
- The proposed exponential operational laws and aggregation operators enhance INS-based decision-making.
- The new methods effectively address uncertainty in decision parameters.
- The approach provides a robust framework for complex selection problems, such as global supplier evaluation.
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