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A Double Deep Q-Network-Enabled Two-Layer Adaptive Work Package Scheduling Approach

In: Proceedings of the 27th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Yaning Zhang

    (Northwestern Polytechnical University
    The Hong Kong Polytechnic University)

  • Xiao Li

    (The Hong Kong Polytechnic University)

  • Chengke Wu

    (The Hong Kong Polytechnic University
    Chinese Academy of Sciences)

  • Zhi Chen

    (Northwestern Polytechnical University)

Abstract

Adaptive project scheduling is paramount for project success. However, it is challenging for industrialized construction (IC) projects to their fragmentation with spatial-temporal distributed work packages (e.g., tasks in production, transportation, and on-site assembly). To achieve adaptive project scheduling in IC, this study proposes a double deep Q-network (DDQN)-enabled two-layer adaptive work package (D2-TAWP) approach. First, the project scheduling process is transformed into a Markov decision process to model the sequential decision-making process of scheduling; Second, a two-layer adaptive scheduling approach is developed to schedule tasks of work packages dynamically. Finally, the effectiveness of the D2-TAWP approach is validated by experimental simulation. The results indicate that the D2-TAWP approach can effectively perform work package scheduling compared to traditional heuristics, which paves the way for the next-generation distributed scheduling of IC projects.

Suggested Citation

  • Yaning Zhang & Xiao Li & Chengke Wu & Zhi Chen, 2023. "A Double Deep Q-Network-Enabled Two-Layer Adaptive Work Package Scheduling Approach," Lecture Notes in Operations Research, in: Jing Li & Weisheng Lu & Yi Peng & Hongping Yuan & Daikun Wang (ed.), Proceedings of the 27th International Symposium on Advancement of Construction Management and Real Estate, pages 1027-1041, Springer.
    • Handle: RePEc:spr:lnopch:978-981-99-3626-7_79
    DOI: 10.1007/978-981-99-3626-7_79
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