Chopra / Dutta / Prakash Verma | Quantum Computing and Artificial Intelligence in Logistics and Supply Chain Management | Buch | 978-1-032-79811-0 | sack.de

Buch, Englisch, 448 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Advances in Digital Technologies for Smart Applications

Chopra / Dutta / Prakash Verma

Quantum Computing and Artificial Intelligence in Logistics and Supply Chain Management


1. Auflage 2025
ISBN: 978-1-032-79811-0
Verlag: Taylor & Francis Ltd

Buch, Englisch, 448 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Advances in Digital Technologies for Smart Applications

ISBN: 978-1-032-79811-0
Verlag: Taylor & Francis Ltd


Quantum Computing in Logistics and Supply Chain Management discusses the transformative potential of quantum computing in reshaping the landscape of supply chain management. It bridges the gap between these two dynamic fields, offering a comprehensive guide to the application of quantum principles in supply chain operations. Through detailed examples and case studies, it highlights how quantum computing can tackle industry-specific issues, such as managing global supply chain disruptions, enhancing production schedules, and enabling real-time decision-making. This book is for researchers, professionals, and technologists interested in quantum computing and supply chain practices.

- Provides an in-depth analysis of quantum computing technologies and their capacity to solve complex optimisation problems at scales unimaginable with traditional computing

- Examines the impact of quantum computing on manufacturing and logistics, with a focus on sectors such as automotive and aerospace

- Real-world scenarios illustrate how quantum solutions can streamline operations and drive efficiency

- Explores quantum algorithms and their use in addressing challenges like route optimisation, inventory management, and demand forecasting, offering strategies to reduce costs and improve resilience

- Considers the current limitations, ethical implications, and the path to widespread adoption of quantum computing in supply chains, emphasising the need for interdisciplinary collaboration

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Zielgruppe


Postgraduate

Weitere Infos & Material


1. Artificial Intelligence in Supply Chain Management: Theory and its Applications 2. Quantum Advancements in Logistics: Transforming Operations through Integrated Quantum Computing 3. Exploring the Use of Quantum Algorithms for Logistics Optimization 4. Quantum Computing in Risk Management and Supply Chain Resilience 5. Industry 4.0 and Supply Chain Sustainability: Insights from Case Studies 6. Quantum Computing and Personalized Digital Marketing: Pioneering the Future of Hyper-Personalized Customer Engagement 7. Optimizing Customer Value through Hybrid Supply Chain Strategies: A Comprehensive Exploration of Lean, Agile, and Leagile Approaches 8. Quantum Leap in Quick Commerce: Harnessing Quantum Computing for Sustainable and Efficient Logistics 9. Real-Time Object Detection System Using AI in Digital Electronics 10. Cross-Domain Object Detection: Adapting Pre-trained Models for Different Visual Domains 11. Enhanced Convolutional Neural Network for Automatic Image Tampering Detection and Localization towards Image Forensics 12. Analyzing View-based 3D Object Classification Using ML Algorithms 13. Designing an AI-Driven Fashion Item Recommender System 14. Content-Based Music Recommendation System Using K-Means Clustering Algorithm 15. Placement Prediction with Machine Learning Models and Flask App 16. Quantifying the Digital Frontier: Frameworks and Challenges in Measuring the Digital Economy 17. Characterization and Prediction of Cold Sprayed Zinc Flake Coating Thickness on Mild Steel Plate Using Quantum Fuzzy Inference System 18. Smart Gas Safety and Air Quality Monitoring 19. Innovative Approaches to Secure Communication: Case Studies Using Matrices and Different Perspectives in Methodological Insights 20. Design Considerations for Microwave RF Energy Harvesting Systems with Applications in the Internet of Things: A Detailed Analysis 21. Enhanced Inventory and Security Monitoring in Supply Chain Logistics Using Sensor-Based Detection Systems 22. Basic CMOS Buffer Design and Enhanced Low Power CMOS Buffer Design 23. Role of Mathematics and Statistics in Cybersecurity 24. Representation of Soft Sets and Soft Topology as Graphs 25. Quantum-Blockchain Scheme in Fraud Detection and Risk Management Resilience 26. Organic Farming-Based Farming System for Sustainability and Better Profitability 27. Quantum-Enhanced Feature Extraction for Smart Logistics and Transportation Systems 28. A Review on Micro and Nanofabrication Methods and Its Applications 29. Quantum-Enhanced Customer Retention: Leveraging Predictive Analytics for Optimized Supply Chain Strategies 30. Modeling and Analysis of Vehicle Load Optimization and Scheduling 31. Elevating Project Manager Responsibilities in Construction Projects through Augmented and Virtual Reality Integration


Pushan Kumar Dutta is an Assistant Professor at Amity University, Kolkata, India. He holds a Ph.D. and specialises in Electronics and Communication Engineering, AI, and digital transformation. He has edited over 30 books and contributed extensively to research on Industry 4.0/5.0, AI in healthcare, IoMT, quantum computing, and digital manufacturing. As Series Editor for "Sustainable Industrial Engineering Systems," he has published in predictive analytics, edge computing, and data mining, with a focus on smart healthcare and earthquake studies. A recipient of the Venus International Faculty Award (2018), he holds two patents and has been recognised as a “Mentor of Change” by NITI Aayog.

Pronaya Bhattacharya is an Associate Professor in the Computer Science and Engineering Department at Amity School of Engineering and Technology, Amity University, Kolkata, India. He holds a Ph.D. from Dr. A. P. J. Abdul Kalam Technical University, Lucknow, India. With over 10 years of academic experience, he has authored more than 140 research papers in SCI journals and IEEE conferences. His research focuses on healthcare analytics, optical switching, federated learning, blockchain, and IoT. Dr Bhattacharya is listed among the top 2% of scientists by Stanford University.

Jai Prakash Verma is an Associate Professor in the Computer Science and Engineering Department at the Institute of Technology, Nirma University, India. He holds a Ph.D. from Charusat University, Changa, India. Specialising in Data Mining, Big Data Analytics, and Machine Learning, he has contributed extensively to research through conferences and journal publications. A recognised PhD guide, he currently supervises three PhD scholars and coordinates training programs for Indian Navy officers and ISRO scientists.

Ashok Chopra is the Registrar and Program Chair for Ph.D. at Amity University Dubai and an Associate Professor at Amity Business School, Dubai, UAE. He holds a Ph.D. and has over 25 years of international industry experience as an academician and corporate trainer. Holding significant administrative roles, he has contributed to research through papers, articles, and books. His expertise includes teaching, training, and designing learning environments for diverse educational backgrounds.

Neel Kanth Kundu is an Assistant Professor at the Centre for Applied Research in Electronics, Indian Institute of Technology Delhi, India. He holds a Ph.D. from The Hong Kong University of Science and Technology (HKUST). His research focuses on signal processing for 6G wireless communications, quantum communications, and quantum information processing. He has held postdoctoral positions at HKUST and The University of Melbourne and has received the INSPIRE Young Faculty Fellowship and the Hong Kong Ph.D. Fellowship.

Khursheed Aurangazeb is an Associate Professor in the Department of Computer Engineering at the College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia. He holds a Ph.D. in Electronics Design from Mid Sweden University, Sweden. With over 17 years of experience in data analytics, machine learning, and embedded systems, he has authored over 90 publications and led multiple research projects. His research focuses on embedded systems, signal processing, and machine learning applications in smart grids, precision agriculture, and healthcare.



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