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© 2015

Handbook of Genetic Programming Applications

  • Amir H. Gandomi
  • Amir H. Alavi
  • Conor Ryan
Book

Table of contents

  1. Front Matter
    Pages i-xi
  2. Overview of Genetic Programming Applications

    1. Front Matter
      Pages 1-1
    2. Penousal Machado, João Correia, Filipe Assunção
      Pages 3-36
    3. E. Fallah-Mehdipour, O. Bozorg Haddad
      Pages 59-70
    4. A. Zahiri, A. A. Dehghani, H. Md. Azamathulla
      Pages 71-97
    5. Renu Vyas, Purva Goel, Sanjeev S. Tambe
      Pages 99-140
    6. Seyyed Soheil Sadat Hosseini, Alireza Nemati
      Pages 141-154
    7. António Leitão, Penousal Machado
      Pages 155-177
  3. Specialized Applications

    1. Front Matter
      Pages 179-179
    2. William B. Langdon
      Pages 181-220
    3. Stanisław Deniziak, Leszek Ciopiński, Grzegorz Pawiński
      Pages 221-244
    4. Conor Ryan, Jeannie Fitzgerald, Krzysztof Krawiec, David Medernach
      Pages 245-287
    5. Mehdi Mousavi, Alireza Azarbakht, Sahar Rahpeyma, Ali Farhadi
      Pages 289-307
    6. Pijush Samui, Yıldırım Dalkiliç, J Jagan
      Pages 345-357

About this book

Introduction

This contributed volume, written by leading international researchers, reviews the latest developments of genetic programming (GP) and its key applications in solving current real world problems, such as energy conversion and management, financial analysis, engineering modeling and design, and software engineering, to name a few. Inspired by natural evolution, the use of GP has expanded significantly in the last decade in almost every area of science and engineering. Exploring applications in a variety of fields, the information in this volume can help optimize computer programs throughout the sciences. Taking a hands-on approach, this book provides an invaluable reference to practitioners, providing the necessary details required for a successful application of GP and its branches to challenging problems ranging from drought prediction to trading volatility. It also demonstrates the evolution of GP through major developments in GP studies and applications. It is suitable for advanced students who wish to use relevant book chapters as a basis to pursue further research in these areas, as well as experienced practitioners looking to apply GP to new areas. The book also offers valuable supplementary material for design courses and computation in engineering.

Keywords

Engineering modeling Evolutionary computation Formulation Gene expression programming Genetic programming Genetically improved software Key applications Real-world problems Simulation Symbolic regression

Editors and affiliations

  • Amir H. Gandomi
    • 1
  • Amir H. Alavi
    • 2
  • Conor Ryan
    • 3
  1. 1.BEACON Center for the Study of Evolution in ActionMichigan State UniversityEast LansingUSA
  2. 2.Department of Civil & Environmental EngineeringMichigan State UniversityEast LansingUSA
  3. 3.Department of Computer Science and Information SystemsUniversity of LimerickLimerickIreland

Bibliographic information

  • Book Title Handbook of Genetic Programming Applications
  • Editors Amir H. Gandomi
    Amir H. Alavi
    Conor Ryan
  • DOI https://doi.org/10.1007/978-3-319-20883-1
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Hardcover ISBN 978-3-319-20882-4
  • Softcover ISBN 978-3-319-36313-4
  • eBook ISBN 978-3-319-20883-1
  • Edition Number 1
  • Number of Pages XI, 593
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Artificial Intelligence
    Computational Intelligence
  • Buy this book on publisher's site
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Reviews

“The editors of this handbook have done a good job in producing a consistent book despite the diversity of topics and contributions. The chapters of the book are self-contained and may be read independently of other chapters. … I strongly recommend this handbook for engineers, practitioners, computer science researchers, and libraries. It will be suitable for advanced students for selecting research problems. It will surely help experienced practitioners seeking to apply GP to new areas.” (S. V. Nagaraj, Computing Reviews, February, 2017)