Neutrosophic aggregation operators and their applications in the software site selection

Area of Science:

• Decision Sciences
• Information Science
• Mathematics

Background:

• Conventional neutrosophic sets (NS) struggle with managing membership degree influence during aggregation.
• Existing models lack robust mechanisms to balance membership degree (MD), indeterminacy membership degree (IMD), and non-membership degree (NMD).

Purpose of the Study:

• To extend the concept of neutrosophic sets by introducing the $$ neutrosophic set ($$ NS).
• To develop a new Multiple Criteria Decision Making (MCDM) model that effectively handles the influence of MD, IMD, and NMD using specific parameters.
• To introduce novel aggregation operators for combining $$ neutrosophic information.

Main Methods:

• Introduction of the $$ neutrosophic set ($$ NS) with defined operational laws.
• Development of a series of aggregation operators (AOs) tailored for $$ neutrosophic information.
• Formulation of a new MCDM model utilizing the proposed AOs.

Main Results:

• The proposed $$ NS framework effectively manages the influence of membership, indeterminacy, and non-membership degrees.
• A case study on software office location selection demonstrates the practical applicability and effectiveness of the new MCDM model.
• The developed aggregation operators successfully combine $$ neutrosophic information for decision-making.

Conclusions:

• The introduced $$ neutrosophic set and MCDM model offer a significant advancement over existing approaches.
• The model's validity and effectiveness are confirmed through comparative analysis, highlighting its potential for real-life decision challenges.
• This research provides a robust framework for enhancing decision-making processes involving uncertain and imprecise information.