Applications of Firefly Algorithm and its Variants

Case Studies and New Developments

  • Nilanjan Dey

Part of the Springer Tracts in Nature-Inspired Computing book series (STNIC)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Nilanjan Dey, Jyotismita Chaki, Luminița Moraru, Simon Fong, Xin-She Yang
    Pages 1-28
  3. Cristina Bianca Pop, Viorica Rozina Chifu, Eric Dumea, Ioan Salomie
    Pages 53-74
  4. Jai Kotia, Rishika Bharti, Adit Kotwal, Ramchandra Mangrulkar
    Pages 147-171
  5. Neeraj Gupta, Mahdi Khosravy, Om Prakash Mahela, Nilesh Patel
    Pages 193-219
  6. Venkatesan Rajinikanth, Nilanjan Dey, Ergina Kavallieratou, Hong Lin
    Pages 221-235
  7. Krishna Gopal Dhal, Samarendu Sahoo, Arunita Das, Sanjoy Das
    Pages 237-266

About this book


The book discusses advantages of the firefly algorithm over other well-known metaheuristic algorithms in various engineering studies. The book provides a brief outline of various application-oriented problem solving methods, like economic emission load dispatch problem, designing a fully digital controlled reconfigurable switched beam nonconcentric ring array antenna, image segmentation, span minimization in permutation flow shop scheduling, multi-objective load dispatch problems, image compression, etc., using FA and its variants. It also covers the use of the firefly algorithm to select features, as research has shown that the firefly algorithm generates precise and optimal results in terms of time and optimality. In addition, the book also explores the potential of the firefly algorithm to provide a solution to traveling salesman problem, graph coloring problem, etc


Firefly Algorithm Optimization Nature-inspired Computing Meta-heuristics Optimization Methodology Convolutional Neural Network

Editors and affiliations

  • Nilanjan Dey
    • 1
  1. 1.Department of Information TechnologyTechno India College of TechnologyKolkataIndia

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