Supplier Selection and Evaluation Based on Grey Correlation Degree and TOPSIS

Abstract

As logistic entity providers of supply chain, suppliers play a crucial role in assuring the smooth running of production and logistics, and realizing on time delivery of client orders. Proper selection of suppliers can not only reduce operations cost but also determine client order response speed, corporate flexibility, and product delivery, etc., hence having great impact on corporate competitiveness. This paper proposes supplier selection decision-making method based on grey correlation degree and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). By introducing grey correlation degree to traditional TOPSIS and combining grey correlation degree and traditional Euclidean distance, a new relative closeness is built, which reflects position relation between ideal solution and negative ideal solution, and similarity difference of data curve. With all the information above serving as the basis of solution order preference, evaluation on supplier optimal solution is thus realized. Simulation results indicate that the decision-making method by combination of grey correlation degree and TOPSIS can get rid of errors caused by subjective factors using one single method, improve reliability of selection solution evaluation, and have a great value of application.