Springer Optimization and Its Applicatio Handbook of Ai-Driven Scheduling and Planning: Advances, Challenges, and Industrial Applications, Book 273, (Hardcover)

This book provides a comprehensive exploration of AI-driven scheduling, integrating cutting-edge artificial intelligence (AI) techniques with traditional scheduling frameworks to optimize resource allocation, decision-making, and operational efficiency. As industries face increasing complexity in scheduling--ranging from manufacturing and logistics to healthcare and workforce management--AI offers transformative solutions that enhance adaptability, scalability, and automation.<p></p> The book is structured into four key sections: <p></p> Foundations of AI-Driven Scheduling--Lays the groundwork for scheduling methodologies, including the Theory of Constraints (TOC) and its evolution with AI.<p></p> AI Techniques for Scheduling and Optimization--Covers machine learning, reinforcement learning, digital twins, process mining, cloud-based scheduling, and multi-objective trade-off management in dynamic scheduling environments.<p></p> Applications Across Industries--Showcases AI-driven scheduling in smart manufacturing, healthcare, workforce planning, supply chain logistics, and energy management with real-world case studies.<p></p> Challenges, Ethical Considerations, and Future Directions--Discusses issues such as bias in AI scheduling, transparency, regulatory concerns, and the future of autonomous scheduling systems.<p></p> This book addresses a critical problem: traditional scheduling methods struggle with unpredictability, inefficiencies, and limited scalability in fast-changing environments. AI-driven scheduling not only overcomes these challenges but also enables real-time decision-making, predictive optimization, and continuous improvement. By bridging the gap between theory and practice, this book empowers professionals, researchers, and decision-makers to implement AI-driven scheduling solutions effectively.<p></p> Designed for academics, industry professionals, AI researchers, operations managers, and policymakers, this book offers practical insights, theoretical foundations, and future research directions for leveraging AI in scheduling and optimization.<p></p>

• Springer Optimization and Its Applicatio Handbook of Ai-Driven Scheduling and Planning: Advances, Challenges, and Industrial Applications, Book 273, (Hardcover)
• Author: Michel Fathi
• ISBN: 9783032285539
• Format: Hardcover
• Publication Date: 2026-09-11
• Page Count: 725