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Genetic research

Scheduling Optimization for Laminated Door Machining Shop Using Improved Genetic Algorithm

Strategic Insights

— 1 min read

Researchers from Nanjing Forestry University have developed an improved genetic algorithm to optimize scheduling in the laminated door machining shop industry. The study finds that the proposed algorithm, known as IGGA, outperforms existing metaheuristics in both best and average relative deviation indices. The research also demonstrates the effectiveness of the proposed model and algorithm in solving the complex problem of laminated door machining shop scheduling, reducing the makespan by 17.91% for a real-world case involving the production of 74 laminated doors.

Key Takeaways:

  • The research focuses on the digital transformation of the wooden-door manufacturing industry, where material preparation planning and production scheduling directly influence the stability and effectiveness of the manufacturing system.
  • The proposed IGGA algorithm is an improved genetic algorithm fused with strategies of the improved heuristic algorithm, local search, variable neighborhood search with multiple critical paths, and iterated greedy search.
  • Comprehensive design of experiments and statistical analyses were conducted to determine appropriate algorithm parameters and verify the substantial improvement of the IGGA.
  • IGGA outperformed other metaheuristics in both the best relative deviation index and the average relative deviation index.
  • The minimal makespan for a real-world case involving the production of 74 laminated doors was 1.1 h, with a 17.91% reduction.
  • The research provides a valuable reference for the rational arrangement of material preparation planning and machining scheduling sequences.
  • The study was supported by the National Key R & D Program of China.
  • The research was conducted by Rongrong Li, Xiaomin Zhou, and Zhihui Wu from Nanjing Forestry University.

Statistics:

  • The proposed IGGA algorithm reduced the makespan by 17.91% for a real-world case involving the production of 74 laminated doors.
  • IGGA outperformed other metaheuristics in both the best relative deviation index and the average relative deviation index.
  • The minimal makespan for a real-world case was 1.1 h.
  • The research was supported by the National Key R & D Program of China.

Sources:

  • Li, R., Zhou, X., & Wu, Z. (2025). Scheduling Optimization for Laminated Door Machining Shop Based On Improved Genetic Algorithm. Computers & Operations Research, 180.
  • National Key R & D Program of China.
  • Nanjing Forestry University.
  • Elsevier. (2025). Computers & Operations Research. (www.journals.elsevier.com/computers-and-operations-research/)

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