A Novel Combinatorial Optimization Strategy with TOPSIS for Smart Manufacturing

Abstract

This study proposes a novel optimization strategy that integrates the combinatorial assignment technique with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), enhancing management efficiency in smart manufacturing. The combinatorial assignment method effectively addresses challenges in decision-making by integrating subjective and objective weight determination, ensuring a more balanced and rational weight distribution. Concurrently, the TOPSIS method facilitates ranking and selecting optimal solutions. Leveraging this integrated approach, the strategy efficiently evaluates employee performance, a critical component of smart manufacturing management. Results demonstrate that this method improves assessment accuracy and fairness, contributing to more effective management practices in the rapidly evolving manufacturing landscape.