Scholarlink

<p>The storage tank is the core resource of the liquid bulk terminal (LBT). Reasonable storage tank scheduling improves the efficiency of unloading and transport operations. The current scheduling paradigms lack information integration and execution feedback, resulting in narrow decision-making horizons and isolated execution processes. Introducing digital twins (DTs) in decision support systems of LBTs enables real-time interaction between decision-making and execution, which helps to address the above gaps. Therefore, this paper investigates a DT-based storage tank scheduling method for unloading and transport operations. The DT-based storage tank scheduling and rescheduling problems are modeled as mixed integer nonlinear programming. A multi-objective optimization algorithm is developed to solve them. Meanwhile, a rescheduling trigger function is designed to respond to common anomalies in the operation. The proposed scheduling method is implemented in a LBT, which is presented as a case study. The results indicate that the proposed scheduling method provides accurate and reliable decision support for LBT operations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Digital twin-based storage tank scheduling for unloading and transport operations at a liquid bulk terminal

  • 期刊论文

  • 发表日期：

    2025年6月7日

查看全文
  • Yuxuan Zhang,
  • Xiangyu Bao,
  • Jiayu Shi,
  • Lei Zhang,
  • Funing Jia,
  • Ziqing Zhang,
  • Dongya Lu,
  • Xue Tang,
  • Liang Chen,
  • Yu Zheng

摘要

The storage tank is the core resource of the liquid bulk terminal (LBT). Reasonable storage tank scheduling improves the efficiency of unloading and transport operations. The current scheduling paradigms lack information integration and execution feedback, resulting in narrow decision-making horizons and isolated execution processes. Introducing digital twins (DTs) in decision support systems of LBTs enables real-time interaction between decision-making and execution, which helps to address the above gaps. Therefore, this paper investigates a DT-based storage tank scheduling method for unloading and transport operations. The DT-based storage tank scheduling and rescheduling problems are modeled as mixed integer nonlinear programming. A multi-objective optimization algorithm is developed to solve them. Meanwhile, a rescheduling trigger function is designed to respond to common anomalies in the operation. The proposed scheduling method is implemented in a LBT, which is presented as a case study. The results indicate that the proposed scheduling method provides accurate and reliable decision support for LBT operations.