Resource Management for Manufacturing Grid Based on Comprehensive Optimization Algorithm

This paper proposes a new method: PCA- Optimal SVM model which is composed of PCA and Optimal SVM to optimize the allocation of manufacturing grid resources through resources allocation data. The model is fit for company in the small sample space. It uses PCA to predigest the input vector and uses Optimal SVM to judge the statement of the company resources. With the model, one or more enterprises could be selected in every process in full lifecycle of product, and the defects in resolving optimal configuration with traditional algorithm model could be omitted. The application case proved that the proposed method can improve the feasibility of the program in optimal configuration, and it is suitable for on-line resource optimal configuration control for manufacturing grid.