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5 produkter
5 produkter
Del 149 - Springer Optimization and Its Applications
Large Scale Optimization in Supply Chains and Smart Manufacturing
Theory and Applications
Inbunden, Engelska, 2019
539 kr
Skickas inom 10-15 vardagar
In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig –Wolfe decomposition, multi-tree decomposition, Van Roy’ cross decomposition and parallel decomposition for mathematical programs such as mixed integer nonlinear programming and stochastic programming. Case studies of large scale optimization in supply chain management, smart manufacturing, and Industry 4.0 are investigated with efficient implementation for real-time solutions. The features of case studies cover a wide range of fields including the Internet of things, advanced transportation systems, energy management, supply chain networks, service systems, operations management, risk management, and financial and sales management. Instructors, graduate students, researchers, and practitioners, would benefit from this book finding the applicability of large scale optimization in asynchronous parallel optimization, real-time distributed network, and optimizing the knowledge-based expert system for convex and non-convex problems.
Del 149 - Springer Optimization and Its Applications
Large Scale Optimization in Supply Chains and Smart Manufacturing
Theory and Applications
Häftad, Engelska, 2020
539 kr
Skickas inom 10-15 vardagar
In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig –Wolfe decomposition, multi-tree decomposition, Van Roy’ cross decomposition and parallel decomposition for mathematical programs such as mixed integer nonlinear programming and stochastic programming. Case studies of large scale optimization in supply chain management, smart manufacturing, and Industry 4.0 are investigated with efficient implementation for real-time solutions. The features of case studies cover a wide range of fields including the Internet of things, advanced transportation systems, energy management, supply chain networks, service systems, operations management, risk management, and financial and sales management. Instructors, graduate students, researchers, and practitioners, would benefit from this book finding the applicability of large scale optimization in asynchronous parallel optimization, real-time distributed network, and optimizing the knowledge-based expert system for convex and non-convex problems.
Del 152 - Springer Optimization and Its Applications
Optimization in Large Scale Problems
Industry 4.0 and Society 5.0 Applications
Inbunden, Engelska, 2019
1 283 kr
Skickas inom 10-15 vardagar
This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the sources of large-scale problems in socio-industrial dilemmas, and the theories that can support these challenges. How theories might also transition to real applications is another question that this book aims to uncover. In answer to the viewpoints expressed by several practitioners and academicians, this book aims to provide both a learning platform which spotlights open questions with related case studies.The relationship between Industry 4.0 and Society 5.0 provides the basis for the expert contributions in this book, highlighting the uses of analytical methods such as mathematical optimization, heuristic methods, decomposition methods, stochastic optimization, and more. The book will prove useful to researchers, students, and engineers in different domains who encounter large scale optimization problems and will encourage them to undertake research in this timely and practical field. The book splits into two parts. The first part covers a general perspective and challenges in a smart society and in industry. The second part covers several case studies and solutions from the operations research perspective for large scale challenges specific to various industry and society related phenomena.
Del 152 - Springer Optimization and Its Applications
Optimization in Large Scale Problems
Industry 4.0 and Society 5.0 Applications
Häftad, Engelska, 2021
1 283 kr
Skickas inom 10-15 vardagar
This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the sources of large-scale problems in socio-industrial dilemmas, and the theories that can support these challenges. How theories might also transition to real applications is another question that this book aims to uncover. In answer to the viewpoints expressed by several practitioners and academicians, this book aims to provide both a learning platform which spotlights open questions with related case studies.The relationship between Industry 4.0 and Society 5.0 provides the basis for the expert contributions in this book, highlighting the uses of analytical methods such as mathematical optimization, heuristic methods, decomposition methods, stochastic optimization, and more. The book will prove useful to researchers, students, and engineers in different domains who encounter large scale optimization problems and will encourage them to undertake research in this timely and practical field. The book splits into two parts. The first part covers a general perspective and challenges in a smart society and in industry. The second part covers several case studies and solutions from the operations research perspective for large scale challenges specific to various industry and society related phenomena.
Handbook of AI-Driven Scheduling and Planning
Advances, Challenges, and Industrial Applications
Inbunden, Engelska, 2026
2 902 kr
Kommande
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.The book is structured into four key sections:Foundations of AI-Driven Scheduling—Lays the groundwork for scheduling methodologies, including the Theory of Constraints (TOC) and its evolution with AI.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.Applications Across Industries—Showcases AI-driven scheduling in smart manufacturing, healthcare, workforce planning, supply chain logistics, and energy management with real-world case studies.Challenges, Ethical Considerations, and Future Directions—Discusses issues such as bias in AI scheduling, transparency, regulatory concerns, and the future of autonomous scheduling systems.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.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.