Book Title:

Advances in Swarm Intelligence: Variations and Adaptations for Optimization Problems


  • Dr. Anupam Biswas, National Institute of Technology Silchar, India (Email:
  • Dr. Seyedali Mirjalili, Torrens University, Australia (Email:
  • Dr. Can Berk Kalayci, Pamukkale University, Turkey (Email:

About the Book

Advances in Swarm Intelligence: Variations and Adaptations for Optimization Problems (swarm21) is an edited book (multi-authored book) to be published at Springer Optimization and Its Applications , Springer book series (Approval Awaited). Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithm development and applications covering almost all disciplines in both science and technology. This book strives to cover all the major SI techniques. This book emphasis on the studies of existing SI techniques, their variants and applications. The book also contains reviews of new developments in SI techniques and hybridizations. Algorithm specific studies covering basic introduction and analysis of key components of these algorithms, such as convergence, balance of solution accuracy, computational costs, tuning and control of parameters. Application specific studies incorporating the ways of designing objective functions, solution representation and constraint handling. The book also includes studies on application domain specific adoptions in the SI techniques.

Topics include, but not limited to…

Swarm Intelligence Techniques:

  • Particle swarm optimization,
  • Ant colony optimization,
  • Cuckoo search algorithm,
  • Bacterial foraging algorithm,
  • Flower pollination algorithm,
  • Firefly algorithm,
  • Artificial bee colony,
  • Moth-flame optimization,
  • Gray wolf optimizer,
  • Bat algorithm,
  • Glowworm swarm optimization,
  • Cockroach swarm optimization,
  • Intelligent water drop,
  • Shuffled frog leaping
  • Self-Organizing Migrating Algorithm

Major Application Areas:

  • Major optimization problems of electrical and power systems,
  • Major optimization problems of electronics and communication engineering,
  • Major optimization problems of mechanical and civil engineering,
  • Machine learning and Deep learning,
  • Robotics and expert systems,
  • Social network analysis,
  • Pattern recognition,
  • Speech processing
  • Image processing,
  • Bioinformatics and health informatics,
  • Manufacturing and operation research

Tentative Table of Contents

1. Introduction to Swarm Intelligence
2. Introductory studies of Swarm Intelligence Techniques
3. Optimization Problems and Swarm Intelligence
4. Analysis of key components of Swarm Intelligence Techniques
5. Studies on Tuning of Parameters, Computation cost and Convergence
6. Studies on Adaptation of Swarm Intelligence from the perspective of Applications
7. Application Specific Studies covering solution representation, objective functions
and constraints
8. New Swarm Intelligence Techniques
9. Hybridization of Swarm Intelligence with Genetic algorithm
10. Hybridization of Swarm Intelligence with Bio-inspired optimization Techniques
11. Hybridization of Swarm Intelligence with Differential Evolution
12. Swarm Intelligence for Machine Learning or Deep Learning
13. Swarm Intelligence for Computer Networking, MANET, WSN
14. Swarm Intelligence for Speech Processing
15. Swarm Intelligence for Image Processing
16. Swarm Intelligence for Bioinformatics
17. Swarm Intelligence for Health Informatics
18. Swarm Intelligence for Manufacturing
19. Swarm Intelligence for Operation Research
20. Swarm Intelligence for Electrical and Power Systems
21. Swarm Intelligence for Electronics and Communication Engineering

Tentative Schedule and Submission Link

Abstract Submission: 20 August, 2021
Abstract Notification: 31 August, 2021
Full Chapter Submission: 31 October, 2021
Full Chapter Notification: 30 November, 2021
Submission link:

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:


All accepted book chapters will be published in Springer Optimization and Its Applications book series (Approval Awaited). This series is indexed in SCOPUS, Web of Science, zbMATH, and Mathematical Reviews. All books published in the series are submitted for consideration in Web of Science. No publication charge.