Book Title: Innovative Nature-inspired Techniques for Solving Complex Problems


  • Dr. Anupam Biswas, National Institute of Technology Silchar, India (Email:
  • Dr. Absalom Ezugwu, University of KwaZulu-Natal, South Africa (Email:
  • Prof. Dr. Fernando Buarque de Lima Neto, University of Pernambuco, Brazil (Email:

About the Book:

Innovative Nature-inspired Techniques for Solving Complex Problems (NatureTech2021) is a edited book (multi-authored book) to be published at Studies in Computational Intelligence (SCI), Springer book series (Approval Awaited). Innovative applications of nature-inspired techniques for solving complex real-world problems have grown manifold in recent years, covering almost all engineering and science disciplines. On the technological front, many new algorithms are designed by taking inspirations from different natural phenomena, resulting in some of the popular algorithms such as Genetic Algorithm (GA) based on Darwin’s principle of survival of the fittest, Ant Colony Optimization (ACO) based on the foraging behaviour of ants, Particle Swarm Optimization (PSO) based on the behaviour of birds flocking in swarms and many more. On the application front, irrespective of the source of inspirations, nature-inspired algorithms are suitable for most of the challenging applications dealing with current complexities of life in this 21st century. This book strives to cover some of the major problems of application domains such as Engineering, Computer Science, Social Sciences, and Natural Sciences. Special attention is drawn to the technical fields of Machine learning, Deep learning, Robotics, Natural Language Processing, Image Processing, Bioinformatics, IOT and Industrial application, as well as Operation Research and Logistics. The book primarily focuses on the practical challenges that are faced while applying nature-inspired algorithms to specific problems of above mentioned application areas.

Tentative Schedule and Submission Link

Abstract Submission: 30 September, 2021
Full Chapter Submission: 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 chapters must be original and not simultaneously submitted to another book, journal or conference.
  • Chapters should not exceed plagiarism of 10% excluding references.
  • Chapter length 15-25 pages.
  • Chapter must include publicly available repository (e.g., GitHub) with the code and data of the chapter.
  • Chapters should be formatted using Springer overleaf template


All accepted book chapters will be published in Studies in Computational Intelligence (SCI) book series (Approval Awaited). This series is indexed in SCOPUS, DBLP, WTI Frankfurt eG, zbMATH, SCImago. All books published in the series are submitted for consideration in Web of Science.