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Updated: Jan 19, 2026

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A novel complex network based dynamic rule selection approach for open shop scheduling problem with release dates.

Zi Long Zhuang1, Zhi Yao Lu1, Zi Zhao Huang1

  • 1School of Mechanical Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China.

Mathematical Biosciences and Engineering : MBE
|September 11, 2019
PubMed
Summary
This summary is machine-generated.

This study addresses dynamic open shop scheduling problems with release dates using heuristic algorithms. A novel complex network approach dynamically selects scheduling rules for efficient task allocation.

Keywords:
complex networkdynamic rule selectionheuristic rulenode traversal orderopen shop

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Area of Science:

  • Operations Research
  • Computer Science
  • Industrial Engineering

Background:

  • The open shop scheduling problem (OSSP) optimizes resource and task allocation.
  • Dynamic task arrivals significantly increase OSSP complexity, especially with release dates.
  • Heuristic algorithms show greater promise than metaheuristics for large-scale dynamic OSSPs.

Purpose of the Study:

  • To develop a framework for describing the OSSP.
  • To propose a complex network model for OSSP.
  • To introduce a dynamic rule selection approach for OSSPs with release dates.

Main Methods:

  • A general scheduling object framework was developed.
  • A complex scheduling network model was established, transforming OSSP into node traversal optimization.
  • Six heuristic rules were proposed, and a dynamic rule selection approach was developed based on real-time production status.

Main Results:

  • The proposed heuristic rules demonstrated acceptable performance in experimental evaluations.
  • The complex network-based dynamic rule selection approach proved feasible for dynamic OSSP.
  • The method effectively switches scheduling rules based on real-time production status.

Conclusions:

  • The developed framework and complex network model provide a structured approach to OSSP.
  • The dynamic rule selection method offers an effective solution for large-scale dynamic open shop scheduling problems with release dates.
  • This research contributes to optimizing scheduling in dynamic manufacturing environments.