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Design Method: Deep Operations Research

In: Intelligent Manufacturing Engineering

Author

Listed:
  • Yong Li

    (Shandong University of Science and Technology, College of Mechanical and Electronic Engineering)

  • Xunchen Liu

    (Shandong University of Science and Technology, College of Mechanical and Electronic Engineering)

  • Shanling Han

    (Shandong University of Science and Technology, College of Mechanical and Electronic Engineering)

  • Jian‘gang Gao

    (Ocean University of China, Faculty of Information Science and Engineering)

Abstract

What is the product of the IME system?—Guidelines. How does the system produce guidelines?—Deep Operations Research (DOR). The value of the IME system lies in uncovering the underlying laws and innovative guidelines that govern enterprise operations. Intelligent Manufacturing Engineering: Deep Operations Research is grounded in the DOR framework proposed by the authors. This method employs the quadflow, including quality flow, cash flow, information flow, material flow, and more, to represent the heterogeneous tensors of intelligent system nodes. It constructs the community and hierarchical complex network of the system, develops a graph neural network algorithm tailored for IME to extract features, and identifies the intrinsic relations among elements, thereby innovating the operational criteria of the system. To understand the heterogeneous hierarchical complex networks composed of MES, ERP, APS, CRM, WMS, and PLM of IME system, and realize the deep mining of industrial data around production scheduling optimization, logistics path planning, customer relation optimization, product development, and network security. Master the design method of the IME system with DOR as the underlying logic and PyTorch as the platform.

Suggested Citation

  • Yong Li & Xunchen Liu & Shanling Han & Jian‘gang Gao, 2026. "Design Method: Deep Operations Research," Springer Books, in: Intelligent Manufacturing Engineering, chapter 0, pages 393-473, Springer.
    • Handle: RePEc:spr:sprchp:978-981-95-3109-7_5
    DOI: 10.1007/978-981-95-3109-7_5
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