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Integrated dynamic scheduling of shipyard blocks considering adaptive adjustment in stockyard layout.

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Title: Integrated dynamic scheduling of shipyard blocks considering adaptive adjustment in stockyard layout.
Authors: Zhong, Meijing1 (AUTHOR), Li, Chunjin1 (AUTHOR) lcj349@just.edu.cn, Hu, Yuan2,3,4 (AUTHOR), Kang, Chao1 (AUTHOR), Liu, Zan1 (AUTHOR), Guo, Jian5 (AUTHOR), Xie, Yang1 (AUTHOR)
Source: Engineering Optimization. Feb2026, Vol. 58 Issue 2, p394-425. 32p.
Subjects: Shipyards, Scheduling, Reinforcement learning, Construction management, Plant layout, Process optimization
Abstract: The scarcity of space resources and backward scheduling management in block assembly yards have become constraints on shipyard logistics owing to demands in shipbuilding technology and scheduling efficiency. This article proposes a novel integrated dynamic scheduling method for shipyard blocks considering adaptive adjustment in stockyard layout. First, an optimization model is established to minimize the interference block moves. Then, dynamic adaptive layout prioritization rules and multi-strategy block movement policies are introduced for different cases. A heap field dynamic layout method based on a binary search tree and deep reinforcement learning algorithms is integrated to seek optimal scheduling. The proposed algorithm is validated with 50 sets of actual block data, four road types and four stockyard types. The results indicate that the proposed method effectively utilizes stockyard layout while reducing interference blocks during the movement process by 56%. A stockyard aspect ratio of approximately 3.2 yields optimal block scheduling effectiveness. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:The scarcity of space resources and backward scheduling management in block assembly yards have become constraints on shipyard logistics owing to demands in shipbuilding technology and scheduling efficiency. This article proposes a novel integrated dynamic scheduling method for shipyard blocks considering adaptive adjustment in stockyard layout. First, an optimization model is established to minimize the interference block moves. Then, dynamic adaptive layout prioritization rules and multi-strategy block movement policies are introduced for different cases. A heap field dynamic layout method based on a binary search tree and deep reinforcement learning algorithms is integrated to seek optimal scheduling. The proposed algorithm is validated with 50 sets of actual block data, four road types and four stockyard types. The results indicate that the proposed method effectively utilizes stockyard layout while reducing interference blocks during the movement process by 56%. A stockyard aspect ratio of approximately 3.2 yields optimal block scheduling effectiveness. [ABSTRACT FROM AUTHOR]
ISSN:0305215X
DOI:10.1080/0305215X.2025.2466829