The escalating demand for operational efficiency and cost optimization in logistics systems has elevated the necessity for intelligent system upgrades to unprecedented levels. Contemporary logistics ecosystems are witnessing accelerated integration of automated machinery and robotics across core operational nodes including warehousing, sorting, packaging, and transportation. This convergence of human expertise, mechanical automation, and robotic intelligence has given rise to next-generation intelligent logistics systems that prioritize collective system performance over individual component capabilities.
Accurate prediction of systemic performance metrics has emerged as a critical prerequisite for optimal system design and operational control. Conventional analytical methodologies demonstrate inherent limitations in addressing the dynamic complexity of these cyber-physical systems. Digital Twin (DT) technology presents a paradigm-shifting solution, enabling bidirectional synchronization between physical logistics infrastructure and their virtual counterparts through real-time data integration and simulation modeling.
As an innovative technological framework, digital twins facilitate unprecedented fidelity in virtual system representation, proving particularly valuable throughout the lifecycle of logistics systems - from initial design prototyping and system debugging to continuous operational optimization. Recent years have witnessed exponential growth in Logistics Digital Twin (LDT) research and industrial applications, establishing this domain as a focal point in global technological innovation.
This dedicated session aims to present cutting-edge advancements in LDT theory and practice, featuring interdisciplinary research that bridges academic innovation with industrial implementation. Contributions will explore novel methodologies for digital twin development, implementation challenges, and transformative applications in modern logistics ecosystems.
The conference will focus on the following aspects:
Methodologies of combing logistics system and digital twin.
AI for LDT.
Innovative researches of RDT
Advanced application researches of LDT
Performance prediction of logistics system via LDT
