Applications of Flower Pollination Algorithm and its Variants

1. Front Matter

   Pages i-xi

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2. Flower Pollination Algorithm: Basic Concepts, Variants, and Applications

   • Shonak Bansal

   Pages 1-24

3. Optimization of Non-rigid Demons Registration Using Flower Pollination Algorithm

   • Sayan Chakraborty, Ratika Pradhan, Sourav Samanta, Amira S. Ashour

   Pages 25-44

4. Adaptive Neighbor Heuristics Flower Pollination Algorithm Strategy for Sequence Test Generation

   • Abdullah B. Nasser, Kamal Z. Zamli, Waheed Ali H. M. Ghanem, Fadhl Hujainah, Nayef. A. M. Alduais, Muhammad Zubair Rehman

   Pages 45-60

5. Implementation of Flower Pollination Algorithm to the Design Optimization of Planar Antennas

   • A. Toktas, D. Ustun, S. Carbas

   Pages 61-85

6. Flower Pollination Algorithm for Slope Stability Analysis

   • A. Öcal, Y. E. Sarıçiçek, O. Pekcan

   Pages 87-111

7. Optimum Sizing of Truss Structures Using a Hybrid Flower Pollinations

   • M. Altun, O. Pekcan

   Pages 113-137

8. Optimizing Reinforced Cantilever Retaining Walls Under Dynamic Loading Using Improved Flower Pollination Algorithm

   • E. B. Tutuş, O. Pekcan, M. Altun, M. Türkezer

   Pages 139-169

9. Multi-objective Flower Pollination Algorithm and Its Variants to Find Optimal Golomb Rulers for WDM Systems

   • Shonak Bansal, Neena Gupta, Arun K. Singh

   Pages 171-196

10. Applications of Flower Pollination Algorithm in Wireless Sensor Networking and Image Processing: A Detailed Study

    • Akalpita Das, Himanish Shekhar Das

    Pages 197-220

11. Flower Pollination Algorithm Tuned PID Controller for Multi-source Interconnected Multi-area Power System

    • K. Jagatheesan, B. Anand, Sourav Samanta

    Pages 221-239

This book presents essential concepts of traditional Flower Pollination Algorithm (FPA) and its recent variants and also its application to find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are extensively implemented to solve a variety of real-world optimization problems due to its adaptability and robustness. FPA is one of the most successful swarm intelligence procedures developed in 2012 and extensively used in various optimization tasks for more than a decade. The mathematical model of FPA is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, FPA has attracted attention of researchers, who are working to find the optimal solutions in variety of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization, and linear/nonlinear optimization problems. Along with the traditional bat algorithm, the enhanced versions of FPA are also considered to solve a variety of optimization problems in science, engineering, and medical applications.

• Flower Pollination Algorithm
• Optimization
• Nature-inspired Computing
• Meta-heuristics
• Wireless Sensor Networking
• Image Processing
• Plant Propagation Algorithm

• Department of Computer Science and Engineering, JIS University, Kolkata, India

  Nilanjan Dey

Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, JIS University, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He is an Adjunct Professor of  Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his PhD from Jadavpur University in 2015. He has authored/edited more than 80 books with Elsevier, Wiley, CRC Press, and Springer, and published more than 300 papers. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence (IGI Global), Associated Editor of IEEE Access, and International Journal of Information Technology (Springer). He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (Springer), Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier), Series Editor ofComputational Intelligence in Engineering Problem Solving and Intelligent Signal Processing and Data Analysis (CRC). His main research interests include medical imaging, machine learning, computer aided diagnosis, data mining, etc. He is the Indian Ambassador of the International Federation for Information Processing—Young ICT Group and Senior member of IEEE.

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