Book Title:
Advances in Swarm Intelligence: Variations and Adaptations for Optimization Problems
Editors
- Dr. Anupam Biswas, National Institute of Technology Silchar, India (Email: anupam@cse.nits.ac.in)
- Dr. Seyedali Mirjalili, Torrens University, Australia (Email: ali.mirjalili@gmail.com)
- Dr. Can Berk Kalayci, Pamukkale University, Turkey (Email: cbkalayci@pau.edu.tr)
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 Studies in Computational Intelligence , Springer book series (Approved). 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: | |
| Abstract Notification: | |
| Full Chapter Submission: | 21 December, 2021 |
| Full Chapter Notification: | 21 January, 2022 |
| Submission link: | https://easychair.org/conferences/?conf=swarm21 |
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
- All chapters must be original and not simultaneously submitted to another book, journal or conference.
- Chapters should not exceed similarity of 10% excluding references.
- Chapter length 15-20 pages.
- Chapters should be formatted using Springer overleaf template https://www.overleaf.com/latex/templates/springer-book-chapter/hrdcrfynnzjn
Publication
All accepted book chapters will be published in Studies in Computational Intelligence book series (Approval Awaited). This series is indexed in SCOPUS, Web of Science, DBLP, WTI Frankfurt eG, zbMATH, SCImago.
No publication charge.
