An algorithm to select the optimal program based on rough sets and fuzzy soft sets

Area of Science:

• Decision Science
• Information Systems
• Computational Intelligence

Background:

• Fuzzy soft sets and rough sets are advanced mathematical tools for handling uncertainty and imprecision.
• Developing optimal decision-making algorithms is crucial in various fields, including business and artificial intelligence.
• Existing methods may not fully capture complex decision-making scenarios involving both vagueness and granularity.

Purpose of the Study:

• To propose a novel algorithm integrating rough sets and fuzzy soft sets for optimal decision program selection.
• To develop a systematic approach for building information systems based on fuzzy soft sets.
• To compute parameter significance and comprehensive weights, incorporating subjective bias.

Main Methods:

• Building information systems using fuzzy soft set theory.
• Calculating parameter significance based on rough set theory.
• Developing an algorithm for comprehensive parameter weighting, including subjective bias.
• Proposing a method for selecting the optimal decision program.

Main Results:

• An effective and rational algorithm for optimal decision program selection was developed.
• The integration of rough sets and fuzzy soft sets provides a robust framework for decision analysis.
• The algorithm successfully computes parameter significance and comprehensive weights.

Conclusions:

• The proposed algorithm offers a powerful approach to optimizing decision programs by combining the strengths of rough and fuzzy soft sets.
• The method demonstrates practical applicability and effectiveness in real-world decision-making scenarios.
• This research contributes to the advancement of intelligent decision support systems.