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Book synopsis

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.

Book details

Book category Books in German Naturwissenschaften, Medizin, Informatik, Technik Mathematik Mathematik - Sonstiges

• Full title: Optimization in Large Scale Problems
• Author: Panos M. Pardalos, Marzieh Khakifirooz
• Language: English
• Binding: Paperback
• Number of pages: 352
• EAN: 9783030285678
• ISBN: 3030285677
• ID: 33530084
• Publisher: Springer International Publishing
• Weight: 598 g
• Dimensions: 235 × 155 × 18 mm
• Date of publishing: 06. January 2021

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