A multi-dimensional evaluation model for power enterprise procurement performance based on fuzzy analytic hierarchy...

Area of Science:

• Operations Research
• Decision Science
• Energy Systems Engineering

Background:

• Power enterprises face unique procurement challenges due to grid reliability, regulatory demands, and long-term investments.
• Traditional evaluation methods struggle with linguistic uncertainty, integrating power-specific criteria, and aggregating stakeholder objectives.
• Existing frameworks lack systematic approaches for complex decision-making in the power sector.

Purpose of the Study:

• To develop a comprehensive multi-dimensional evaluation model for power enterprise procurement.
• To integrate Fuzzy Analytic Hierarchy Process (FAHP) and TOPSIS for enhanced decision support.
• To address limitations of traditional methods in handling uncertainty and power-specific criteria.

Main Methods:

• Integration of Fuzzy Analytic Hierarchy Process (FAHP) for subjective judgment and uncertainty handling.
• Application of TOPSIS for robust ranking based on distance-to-ideal solutions.
• Development of a hierarchical evaluation system with dimensions: cost-benefit, quality, supplier relationship, and risk control.

Main Results:

• The integrated FAHP-TOPSIS model achieved a 23% improvement in consistency ratios.
• Empirical validation showed a closeness coefficient of 0.6651, placing the enterprise at the 73rd industry percentile.
• Sensitivity analysis confirmed model robustness with 96.3% ranking stability; 91.3% accuracy in identifying performance gaps.

Conclusions:

• The developed multi-dimensional model offers enhanced analytical capabilities for strategic procurement in power enterprises.
• The framework systematically addresses linguistic uncertainty and integrates diverse stakeholder objectives.
• It provides a robust tool for continuous improvement and informed decision-making in the energy sector.