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Optimization in Large Scale Problems

Industry 4.0 and Society 5.0 Applications

  • Mahdi Fathi
  • Marzieh Khakifirooz
  • Panos M. Pardalos
Book

Part of the Springer Optimization and Its Applications book series (SOIA, volume 152)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Roadmap of Optimization for Large Scale Problem

  3. Case Studies

    1. Front Matter
      Pages 73-73
    2. Aven Samareh, Mahshid Salemi Parizi
      Pages 97-110
    3. Javier Salmeron, Emily M. Craparo
      Pages 111-127
    4. Nasim Nezamoddini, Faisal Aqlan, Amirhosein Gholami
      Pages 179-199
    5. Haifeng Wang, Qianqian Zhang, Daehan Won, Sang Won Yoon
      Pages 221-242
    6. Shashank Sheshar Singh, Ajay Kumar, Shivansh Mishra, Kuldeep Singh, Bhaskar Biswas
      Pages 255-267
    7. Meigui Yu, Armagan Bayram, Bahriye Cesaret
      Pages 293-304
    8. Satya S. Malladi, Alan L. Erera, Chelsea C. White III
      Pages 319-327
    9. Asmaa Sabiri, Fouad Riane, Sabine Limbourg
      Pages 329-340

About this book

Introduction

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.

Keywords

large scale optimization Benders decomposition Dynamic system management multi-tree decomposition linear programming integer programming stochastic programming nonlinear optimization Industry 4.0 Society 5.0 energy systems advanced transportation networks machine learning

Editors and affiliations

  • Mahdi Fathi
    • 1
  • Marzieh Khakifirooz
    • 2
  • Panos M. Pardalos
    • 3
  1. 1.Department of Industrial and Systems EngineeringMississippi State UniversityStarkvilleUSA
  2. 2.School of Science and EngineeringTecnológico de MonterreyMonterreyMexico
  3. 3.Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-28565-4
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-030-28564-7
  • Online ISBN 978-3-030-28565-4
  • Series Print ISSN 1931-6828
  • Series Online ISSN 1931-6836
  • Buy this book on publisher's site