Digital twin-driven proactive-reactive scheduling framework for port multi-equipment under a complex uncertain environment

IF 3.5 2区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Simulation Modelling Practice and Theory Pub Date : 2024-08-17 DOI:10.1016/j.simpat.2024.103011
Wenfeng Li , Huixian Fan , Lei Cai , Wenjing Guo , Ziteng Wu , Pengfei Yang
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Abstract

The pervasive uncertainties in multiple port equipment scheduling frequently result in container handling delays or ineffective plans. To address the complexities and uncertainties of port multiple equipment integrated scheduling problem, this paper introduces a Digital Twin-driven (DT-driven) proactive-reactive scheduling framework for the first time. This framework is designed to promptly respond to uncertainties in the scheduling process and provide a transparent visualization of operational information. It specifically tackles the integrated scheduling problem of port quay cranes, Intelligent Guided Vehicles (IGVs), and yard cranes, considering uncertainties such as fluctuations in operating time, equipment failures, and IGV route conflicts. By developing a virtual container port simulation, which features a U-shaped port layout and double-cycling mode drawn from real-world scenarios, the paper evaluates the proposed framework's effectiveness. The experimental results demonstrate that the digital twin framework method significantly improves efficiency and conserves energy. Additionally, in large-scale conditions, the makespan difference between the DT-driven approach and the non-DT-driven approach is as much as 19.56 %. In terms of energy consumption savings, the DT-driven approach's scheduling plan can save 3.67 % of energy consumption under large-scale conditions. Moreover, as the fluctuation index increases, the energy consumption savings become even more significant. This paper also discusses the potential implications of adopting this framework for port companies, highlighting its benefits in enhancing operational and energy efficiency and its incorporation into port management systems. The sensitivity analysis can offer guidance to port companies on optimal equipment allocation strategies.

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复杂不确定环境下港口多设备数字孪生驱动的主动-反应调度框架
多港口设备调度中普遍存在的不确定性经常导致集装箱装卸延迟或计划无效。针对港口多设备综合调度问题的复杂性和不确定性,本文首次提出了数字孪生驱动(DT-driven)的主动-反应调度框架。该框架旨在及时应对调度过程中的不确定性,并提供透明的可视化操作信息。它特别解决了港口码头起重机、智能导引车(IGV)和堆场起重机的综合调度问题,考虑了操作时间波动、设备故障和智能导引车路线冲突等不确定因素。通过开发一个虚拟集装箱港口仿真,该仿真具有 U 型港口布局和来自真实世界场景的双循环模式,本文评估了所建议框架的有效性。实验结果表明,数字孪生框架方法显著提高了效率并节约了能源。此外,在大规模条件下,数字孪生驱动方法与非数字孪生驱动方法的有效期差异高达 19.56%。在节省能耗方面,DT 驱动方法的调度计划在大规模条件下可节省 3.67% 的能耗。此外,随着波动指数的增加,能耗节省也会变得更加显著。本文还讨论了采用该框架对港口公司的潜在影响,强调了该框架在提高运营和能源效率以及将其纳入港口管理系统方面的优势。敏感性分析可为港口公司的最佳设备分配策略提供指导。
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来源期刊
Simulation Modelling Practice and Theory
Simulation Modelling Practice and Theory 工程技术-计算机:跨学科应用
CiteScore
9.80
自引率
4.80%
发文量
142
审稿时长
21 days
期刊介绍: The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling. The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas. Paper submission is solicited on: • theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.; • methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.; • simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.; • distributed and real-time simulation, simulation interoperability; • tools for high performance computing simulation, including dedicated architectures and parallel computing.
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