Collection
Special Issue: Modeling, Learning, and Optimization for Smart Manufacturing Logistics: In Memory of Carlo Meloni
Smart manufacturing logistics integrates advanced sensing, learning, and control technologies to modernize the manufacturing industry. This integration has prompted researchers to gain a fresh perspective on the logistics operations and their associated manufacturing processes and develop tools that can analyze large volumes of industrial data and make real-time decisions. To optimize and automate both logistics and manufacturing operations effectively, it's essential to develop innovative approaches that leverage modeling, learning, and optimization technologies to enhance the efficiency of the manufacturing process, ultimately advancing the industry.
To address these challenges, this special issue of Flexible Services and Manufacturing (FSM) Journal aims to showcase recent developments and empirical studies related to modeling, learning, and optimization aiming for smart manufacturing logistics. We welcome papers that present new research contributions in this area, with a focus on real-world examples that demonstrate scientific advances and their practical implications. Topics of interest include, but are not limited to:
• Learning-Based Approaches for Decision-Making
• Big Data Mining and Analytics
• Integration of Optimization, Learning, and Control
• Intelligent Automation: Robotics, AI, and Machine Learning
• Agent-Based Modeling and Computing
• Smart Logistics for Sustainable Manufacturing
• Model-Based and Model-Free Based Predictive Control
• Digital Twin Technology and its Applications
• Coordination for Supply Chain Management
Editors
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Jianbin Xin
Zhengzhou University, China
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Frederik Schulte
Delft University of Technology, The Netherlands
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Wenfeng Li
Wuhan University of Technology, China
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Chun Wang
Concordia University, Canada
