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Optimizing Supply Chains Through Digital Twins: Navigating the Modern Landscape

by Ghaith Rabadi , Bulent Soykan
Save 35% Save 35%
Current price ₹12,690.00
Original price ₹19,523.00
Original price ₹19,523.00
Original price ₹19,523.00
(-35%)
₹12,690.00
Current price ₹12,690.00

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Book cover type: Hardcover
  • ISBN13: 9783032081469
  • Binding: Hardcover
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 265
  • Original Price: EUR 174.39
  • Language: English
  • Edition: N/A
  • Item Weight: 563 grams
  • BISAC Subject(s): Production & Operations Management

Ghaith Rabadi is the Director and a Professor 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 Research Scientist at the Institute for Simulation and Training (IST), 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.

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