This paper proposes a scientific and systematic method for supplier selection to address the limitations of traditional approaches, particularly their subjective weight calculations and limited accuracy in comprehensive evaluations. An integrated model combining the improved Analytic Hierarchy Process (AHP) and Particle Swarm Optimization (PSO) is developed. First, the Delphi method defines four key dimensions and indicators. Then, fuzzy logic enhances the objectivity of AHP weight calculations. Finally, PSO is used to optimize supplier selection under complex multi-criteria decision-making scenarios. Using real data from an automobile manufacturer, the model's performance is evaluated. Results demonstrate improvements in both accuracy and efficiency: the enhanced AHP ensures rational weight assignment, while PSO achieves global optimization. The model identifies Suppliers A, C, and E as top performers, confirming its practical utility. This approach offers actionable decision-making support for automotive enterprises and shows potential for transferable transferability to other industries. Limitations include sample size and adaptability issues, indicating a need for future research to incorporate dynamic optimization and larger datasets to enhance robustness and scalability.
Ben Li (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: