Evolutionary and Swarm Intelligence Algorithms

  • Jagdish Chand Bansal
  • Pramod Kumar Singh
  • Nikhil R. Pal

Part of the Studies in Computational Intelligence book series (SCI, volume 779)

Table of contents

  1. Front Matter
    Pages i-x
  2. Jagdish Chand Bansal, Nikhil R. Pal
    Pages 1-9
  3. Jagdish Chand Bansal
    Pages 11-23
  4. Harish Sharma, Garima Hazrati, Jagdish Chand Bansal
    Pages 43-59
  5. Liang Feng, Yew-Soon Ong, Abhishek Gupta
    Pages 61-84
  6. Kaustuv Nag, Nikhil R. Pal
    Pages 119-141
  7. Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan
    Pages 143-167
  8. S. Elhag, A. Fernández, S. Alshomrani, F. Herrera
    Pages 169-190

About this book


This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.


Computational Intelligence Evolutionary Algorithms Swarm Intelligence Evolutionary Intelligence Swarm

Editors and affiliations

  • Jagdish Chand Bansal
    • 1
  • Pramod Kumar Singh
    • 2
  • Nikhil R. Pal
    • 3
  1. 1.South Asian UniversityNew DelhiIndia
  2. 2.ABV-Indian Institute of Information Technology and ManagementGwaliorIndia
  3. 3.Electronics and Communication Sciences Unit (ECSU)Indian Statistical InstituteKolkataIndia

Bibliographic information

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