Spherical Fuzzy Logarithmic Aggregation Operators Based on Entropy and Their Application in Decision Support Systems.

Area of Science:

• Decision Sciences
• Fuzzy Set Theory
• Operations Research

Background:

• Multi-criteria group decision-making (MCGDM) is complex.
• Spherical fuzzy sets (SFSs) offer a robust framework for uncertainty.
• Existing methods may lack efficiency in handling spherical fuzzy data.

Purpose of the Study:

• To propose a novel method for MCGDM problems using spherical fuzzy sets.
• To introduce new logarithmic operations and operators for SFSs.
• To develop a spherical fuzzy entropy for determining criteria weights.

Main Methods:

• Development of novel logarithmic operations for SFSs.
• Introduction of spherical fuzzy weighted average and geometric operators.
• Proposal of spherical fuzzy entropy for weight determination.
• Analysis of properties like idempotency, boundary, and monotonicity.

Main Results:

• A systematic procedure for spherical fuzzy decision-making problems was established.
• A practical case study validated the proposed method's effectiveness.
• Comparative analysis demonstrated the superiority of the new approach over existing methods.

Conclusions:

• The proposed method is effective and suitable for evaluating alternatives in decision-making.
• The novel logarithmic operations and operators enhance the handling of spherical fuzzy information.
• This research contributes a valuable tool for complex MCGDM scenarios.