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Optimization in Large Scale Problems

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Optimization in Large Scale Problems 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.

About This Edition

ISBN: 9783030285678
Publication date:
Author: Mahdi Fathi, Marzieh Khakifirooz, Panos M Pardalos
Publisher: Springer an imprint of Springer International Publishing
Format: Paperback
Pagination: 340 pages
Series: Springer Optimization and Its Applications
Genres: Optimization
Purchasing and supply management
Mathematical modelling
Maths for engineers
Production and industrial engineering