Aggregation operators of neutrosophic linguistic numbers for multiple attribute group decision making

Area of Science:

• Decision Sciences
• Artificial Intelligence
• Operations Research

Background:

• Symbolic neutrosophic theory provides a framework for uncertainty.
• Neutrosophic linguistic numbers (NLNs) extend this theory.
• Existing methods for decision-making under uncertainty require enhancement.

Purpose of the Study:

• To define basic operational laws and expected values for NLNs.
• To develop NLN weighted arithmetic average (NLNWAA) and NLN weighted geometric average (NLNWGA) operators.
• To establish a multiple attribute group decision-making (MAGDM) method using NLN operators.

Main Methods:

• Definition of NLN operational laws and expected value for ranking.
• Development and property analysis of NLNWAA and NLNWGA operators.
• Construction of a MAGDM framework utilizing the proposed NLN operators.

Main Results:

• Established foundational operations for NLNs.
• Introduced novel NLNWAA and NLNWGA operators with discussed properties.
• Developed a practical MAGDM method applicable in uncertain environments.

Conclusions:

• The proposed NLN-based MAGDM method offers a robust approach for decision-making.
• The developed operators and methods are applicable to real-world problems, such as flexible manufacturing system selection.
• This work contributes to the advancement of decision-making techniques in neutrosophic environments.