Random Forest Classifier for Distributed Multi-plant Order Allocation
This paper focuses on the problem of multi-plant order allocation. It proposes a solution combining a machine learning algorithm and an optimization algorithm. It mainly concentrates on how to apply machine learning classifier to expedite the process of solving this problem in high accuracy. Random Forest classifier and an instance are used to illustrate this method, and the process of the experiment is also represented. Moreover, the result of classification by random forest is analyzed and compared with three other classifiers. The comparison approves that the proposed approach can achieve the problem more efficiently and reasonably.
KeywordsOrder allocation Random forest Multi-plant Accuracy Speed
This work is sponsored by a Research Grant from National Natural Science Foundation of China (71271122) and National Undergraduate Training Program for Innovation and Entrepreneurship (201610055036).
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