Integrating Subjective–Objective Weights Consideration and a Combined Compromise Solution Method for Handling Supplier Selection Issues

• Published in: Systems (Basel) 2023-02, Vol.11 (2), p.74
• Main Author: Chang, Kuei-Hu
• Format: Article
• Language: English
• Subjects: Artificial intelligence; combined compromise solution; Component and supplier management; Decision making; Epidemics; Evaluation; Fast moving consumer goods; Linguistics; Logistics; Logistics management; Methods; Qualitative analysis; Ranking; Site selection; stepwise weight assessment ratio analysis; subjective–objective weights; Suppliers; Supply chains; Sustainable development; third-party logistics; Vendor relations
• ISSN: 2079-8954; 2079-8954
• DOI: 10.3390/systems11020074

The development of artificial intelligence and the recent COVID-19 pandemic as well as the emergence of other diseases has led to dramatic changes in the overall supply chain development. The choice of a suitable supplier will be the key to ensuring sustainable development of the company and the normal operation of the overall supply chain. However, the evaluation data of the supplier selection contains both qualitative and quantitative data simultaneously. In addition, the evaluation information provided by experts often includes some incomplete and hesitant information. These reasons lead to the complexity of supplier selection. Traditional supplier selection calculation methods ignore the objective weight considerations and thus lead to biased assessment results. The main goal of this study is to overcome the limitations of conventional supplier selection methods, fully consider the subjective and objective weights of the evaluation criteria and deal with incomplete information for providing more correct supplier ranking results. A stepwise weight assessment ratio analysis (SWARA) method, the 2-tuple linguistic representation method, and the combined compromise solution (CoCoSo) were applied in this study to solve the problem of supplier selection. To verify the rationality and correctness of the proposed method, the third-party logistics supplier selection was used as the illustrated example in the numerical validation section. The simulation results confirm that the proposed method can effectively deal with supplier selection with unclear information and can provide more reasonable supplier ranking results.