The Logistics Performance Evaluation Based on KPCA-LINMAP Model

摘要

According to the limitation of Principal Components Analysis (PCA) in dealing with the nonlinear data, connecting with the Linear Programming Techniques for Multidimensional Analysis of Preference (LINMAP), this paper presents the Kernel Principal Components Analysis-Linear Programming Techniques for Multidimensional Analysis of Preference (KPCA-LINMAP) model. The weight of each index can be determined in the model, thus it covers the next shortage of PCA. In logistics performance evaluation, the indexes are numerous and the degree of correlation is not high, the model is more appropriate for it than the traditional PCA. At last, the validity and the advantage are verified by an instance.