上海交通大学学报

上海交通大学学报 >

2026 , Vol. 60 >Issue 8: 1266 - 1278

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2025.353

数字孪生与智能设计

基于数字孪生的改进A*HNSA算法在船舶分段吊运任务的应用

  • 齐麟龙 ,
  • 刘立全 ,
  • 王喆 ,
  • 张子绅 ,
  • 朱颖 ,
  • 夏唐斌
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  • 1 上海交通大学 机械与动力工程学院, 上海 200240
    2 清峦福兴工业科技集团有限公司, 山东 枣庄 277500
    3 上海交通大学 航空航天学院, 上海 200240
    4 特殊环境数字制造装备技术创新中心, 四川 绵阳 621900
齐麟龙(2001—),硕士生,从事数字孪生、运筹优化算法、船舶智能制造研究.

收稿日期: 2025-10-22

  修回日期: 2025-12-18

  录用日期: 2026-01-15

  网络出版日期: 2026-04-09

基金资助

国家自然科学基金(72571173);国家自然科学基金(72301169)

收起

Application of Digital Twin-Based Improved A*HNSA Algorithm to Ship Block Hoisting Tasks

  • QI Linlong ,
  • LIU Liquan ,
  • WANG Zhe ,
  • ZHANG Zishen ,
  • ZHU Ying ,
  • XIA Tangbin
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  • 1 School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    2 Qingluan Fuxing Industrial Technology Co., Ltd., Zaozhuang 277500, Shandong, China
    3 School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China
    4 Special Environment Digital Manufacturing Equipment Technology Invitation Center, Mianyang 621900, Sichuan, China

Received date: 2025-10-22

  Revised date: 2025-12-18

  Accepted date: 2026-01-15

  Online published: 2026-04-09

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摘要

船舶分段堆场调度是船舶建造中的关键环节.针对堆场吊运作业效率偏低的问题,本文构建面向分段堆场的数字孪生系统与高保真虚拟仿真环境,提出改进的A*HNSA两阶段优化方法,在数字孪生驱动下联合优化吊运次序与龙门吊路径.基于上海某船厂的真实调度数据,根据调度分段的数量,设置小型、中型、大型3类算例,并与已有方法对比.结果显示,与已有方法相比,该方法在3类算例中总运输距离分别降低3.51%、5.33%、6.79%,总调度时间分别降低3.82%、5.35%、7.07%,显著降低了龙门吊运输成本,提升了求解效率,且满足分段堆场数字孪生系统的在线响应要求.

关键词： 数字孪生; 船舶分段堆场调度; 路径规划; A*算法; 模拟退火算法

本文引用格式

齐麟龙 , 刘立全 , 王喆 , 张子绅 , 朱颖 , 夏唐斌 . 基于数字孪生的改进A*HNSA算法在船舶分段吊运任务的应用[J]. 上海交通大学学报, 2026 , 60(8) : 1266 -1278 . DOI: 10.16183/j.cnki.jsjtu.2025.353

Abstract

Block yard scheduling is a crucial link in ship construction. To address the issue of low efficiency in yard hoisting operations, this paper constructs a digital twin system and a high-fidelity virtual simulation environment for block yards, and proposes an improved two-stage optimization method named A*HNSA. Driven by the digital twin, this method jointly optimizes the hoisting sequence and the gantry crane path planning. Based on the real scheduling data from a shipyard in Shanghai, three types of test cases (small, medium, and large) are established according to the number of scheduling blocks, and comparisons are made with existing methods. The results show that, compared with existing methods in the three types of test cases, the proposed method reduces the total transportation distance by 3.51%, 5.33%, and 6.79% respectively, and shortens the total scheduling time by 3.82%, 5.35%, and 7.07% respectively. It significantly reduces the transportation cost of gantry cranes, improves the solution efficiency, and meets the online response requirements of the block yard digital twin system.

Key words： digital twin; ship block yard scheduling; path planning; A* algorithm; simulated annealing (SA) algorithm

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