This book features keynote speeches, workshops, and parallel sessions that address global challenges and opportunities in supply chains across industries such as agriculture, maritime, healthcare, and smart cities, with a focus on AI-driven solutions, sustainable practices, and technological innovations. The 19th International Congress on Logistics and Supply Chain Management (ICLS2025), hosted by The Hong Kong Polytechnic University, brings together leading academics, industry professionals, and policymakers to explore cutting-edge advancements in logistics and supply chain management. Participants will gain insights into transformative research, network with experts, and contribute to shaping the future of intelligent and resilient supply chain systems.
A Basic Study on SCM AI Applications in Japan.- Research and Application
of Cold Chain Logistics in Agricultural Products Supply Chain.- Graph-based
Product2Task-Worker-Machine Mapping in Modular Construction.- Decoding Market
Signals with Self-adaptive Temporal Modeling in Multi-period
decision-making.- A Quasi-Natural Experiment Study on the Impact of China's
Energy-Consuming Rights Trading (ECRT) on Corporate Financial Performance.-
Design and Improvement of Vibration Tooling Based on Finite Element
Analysis.- Low-Altitude Logistics with Physical Internet.- Measuring the
Performance of Logistics Enterprises Using a Multi-criteria Decision-making
Model.- Optimizing E-commerce Warehouse Operations: Leveraging A and
Dijkstras Algorithms for Efficient Picking Routes.- Building customer
satisfaction in last-mile deliveries in e-commerce pilot study.- Digital
twin-enabled production logistics synchronization for enhancing efficiency
and sustainability in pharmaceutical manufacturing.
Prof. Li Ming is a distinguished scholar specializing in industrial and systems engineering at The Hong Kong Polytechnic University. His research interests include smart logistics, supply chain optimization, and AI-driven decision-making systems. Prof. Li has authored numerous influential publications and actively contributes to leading academic journals as an editor and reviewer. He has received accolades for his contributions to operations research and logistics innovation. His leadership in academia and industry collaborations has made a lasting impact on the development of intelligent supply chain solutions. Cheng Ren is a postdoctoral research fellow in the Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University. He received his Ph.D. degree in control science and engineering from Shanghai Jiao Tong University. His research focuses on industrial digital twin technology, industrial Internet of Things, and automation systems, with applications in manufacturing, aviation, and intelligent logistics. Prof. Pan Shenle is a full professor in sustainable logistics and supply chain management at MINES Paris, PSL University, France. He is also the co-director of the Physical Internet Chair and associate head of the Center for Management Science. Prof. Pan has led over 20 research projects funded by the EU, French national programs, and industrial partners. His research focuses on sustainable logistics, smart city supply chains, and data analytics. Recognized as one of the top 2% scientists globally by Stanford/Elsevier, he continues to shape the future of resilient and green supply chain systems through innovative research and international collaboration. Prof. Huang George Q is a leading expert in industrial and systems engineering at The Hong Kong Polytechnic University. With a focus on advanced manufacturing, logistics, and smart supply chains, he has made pioneering contributions to the integration of digital technologies in industrial settings. Prof. Huangs extensive research portfolio includes international collaborations with institutions across Europe and Asia. A highly cited researcher, he holds editorial roles in multiple prestigious journals and has received numerous awards for his groundbreaking work in smart manufacturing and sustainable logistics systems.
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