Research on supply chain performance assessment based on least squares support vector machines

The performance assessment of supply chain plays an important role in supply chain management of enterprises. In this paper, we set up performance evaluation index system including business process, financing, client, study and development of supply chain by balanced scorecard (BSC) method. The comprehension evaluation model of supply chain performance based on least squares support vector machines (LS-SVM) is proposed. In order to illustrate the effectiveness of the model, we evaluated the performance of one manufacturing industry supply chains by LS-SVM model and BP neural network method. The case shows that the LS-SVM model is more effective than the BP neural network method. The case shows that the model is effective and can provide a basis for decision-making for enterprises improving supply chain´s overall performance.