Optimizing Supply Chains Through Digital Twins

Ghaith Rabadi is a Professor and Graduate Programs Director in the Modeling and Simulation programs at the School of Modeling, Simulation, and Training (SMST), University of Central Florida (UCF), USA. His research focuses on modeling complex systems and using optimization, simulation, and AI to find optimal and near-optimal solutions to complex systems including multimodal transportation systems, production, ports, disaster response logistics, and healthcare. He is a recipient of the NASA Faculty Fellowship, NASA Software Invention Award, the NASA Board Action Invention Award, as well as the Fulbright Specialist Program Award and NATO Innovation Challenge. His research has been funded by various agencies including NASA, NATO, Department of Homeland Security, Virginia Port Authority, MITRE Corporation, STIHL, Sentara Hospitals and Qatar Foundation. He is the co-founder and currently the Chief Editor of the International Journal of Planning and Scheduling.Bulent Soykan is a Postdoctoral Scholar at the School of Modeling, Simulation, and Training, University of Central Florida (UCF), USA. His research focuses on large-scale optimization, system simulation and modeling, digital twins, reinforcement learning, supply chains, transportation & logistics. He has a background in operations research and systems analysis, with specific training and expertise in modeling and simulation. He develops comprehensive, usable digital twins to support decision making to increase automation in solving complex real-world problems in supply chains, manufacturing, and various other domains. To accomplish this, he integrates principles and knowledge from the fields of operations research and data science, as well as drawing from various AI fields, such as automated planning, sequential decision making, machine learning, and deep reinforcement learning.

• Introduction.- Digital Twin in Supply Chain Management: A Comprehensive Bibliometric Review.- Harnessing the Power of Simulation in Supply Chain Digital Twins.- Supply Chain Digital Twin Application: Control Tower.- The Digital Backbone of Modern Supply Chains: Enabling Technologies for Digital Twins.- Modeling Supply Chain Ecosystem Architecture to Support Digital Twins.- A Supply Chain Digital Twin Architecture for Semiconductor Industry.- A framework for Supply Chain Simulation and Digital Twinning.- Navigating The Modern Landslide”: The Agent-Based View Towards Supply Chain Immunity and Digital Twin Optimization - A Use Case with XMPro.- Uncertainty Quantification in Digital Twin Simulations.- Digitalizing the Automotive Assembly Line: A Case Study for Enhancing Supply Chain Efficiency with Digital Twin Technology.- Digital Twins for Hyperconnected City Logistics.- Integrating AI and ML in Supply Chain Digital Twins: Bridging Potential and Foundational Research Gaps.