An Approach to Determining Attribute Weights Based on Integrating Preference Information on Attributes with Decision...

Area of Science:

• Operations Research
• Decision Science

Background:

• Multiple attribute decision-making (MADM) problems often involve uncertainty and subjective preferences.
• Existing methods may not fully capture the nuances of interval data and complex attribute interdependencies.

Purpose of the Study:

• To develop a robust method for determining attribute weights in interval MADM problems.
• To effectively integrate diverse preference information, including linguistic terms and interval numbers.
• To enhance decision-making accuracy by combining subjective and objective weighting approaches.

Main Methods:

• Normalization and aggregation of preference information (orderings, linguistic terms, interval numbers) into group opinions.
• Optimization model formulation to calculate subjective attribute weights, incorporating inequality constraints.
• Application of the entropy method to compute objective attribute weights from the interval decision matrix.
• Integration of subjective and objective weights to reflect both preference and data-driven insights.

Main Results:

• A comprehensive approach for attribute weight determination in interval MADM is proposed.
• The method successfully integrates subjective preferences with objective data from the decision matrix.
• Demonstrated effectiveness through a practical example, validating the approach's utility.

Conclusions:

• The proposed method provides a balanced way to determine attribute weights by considering both subjective and objective factors.
• This approach enhances the reliability and accuracy of decision-making in complex interval environments.
• Offers a valuable tool for researchers and practitioners dealing with interval MADM challenges.