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Random Forest Classifier for Distributed Multi-plant Order Allocation

  • Si-han Wang
  • Wen-di Ren
  • Yi-fan Zhang
  • Feng LiangEmail author
Conference paper

Abstract

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.

Keywords

Order allocation Random forest Multi-plant Accuracy Speed 

Notes

Acknowledgements

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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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Si-han Wang
    • 1
  • Wen-di Ren
    • 2
  • Yi-fan Zhang
    • 3
  • Feng Liang
    • 1
    Email author
  1. 1.Department of Management Science and EngineeringNankai UniversityTianjinPeople’s Republic of China
  2. 2.School of Data and Computer ScienceSun Yat-Sen UniversityGuangzhouPeople’s Republic of China
  3. 3.Department of MathematicsNankai UniversityTianjinPeople’s Republic of China

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