Handbook of Moth-Flame Optimization Algorithm
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Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications

Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications

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International Edition


About the Book

Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges, including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters. Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges. Key Features: Reviews the literature of the Moth-Flame Optimization algorithm Provides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithm Proposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problems Demonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithm Introduces several applications areas of the Moth-Flame Optimization algorithm This handbook will interest researchers in evolutionary computation and meta-heuristics and those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas.

Table of Contents:
Section I Moth-Flame Optimization Algorithm for Different Optimization Problems Chapter 1 ◾ Optimization and Meta-heuristics Seyedali Mirjalili Chapter 2 ◾ Moth-Flame Optimization Algorithm for Feature Selection: A Review and Future Trends Qasem Al-Tashi, Seyedali Mirjalili, Jia Wu, Said Jadid Abdulkadir, Tareq M. Shami, Nima Khodadadi, and Alawi Alqushaibi Chapter 3 ◾ An Efficient Binary Moth-Flame Optimization Algorithm with Cauchy Mutation for Solving the Graph Coloring Problem Yass ine Meraihi, Asm a Benmess aoud Gabis, and Seyedali Mirjalili Chapter 4 ◾ Evolving Deep Neural Network by Customized Moth-Flame Optimization Algorithm for Underwater Targets Recognition Mohamm ad Khishe, Mokhtar Mohamm adi, Tarik A. Rashid, Hoger Mahmud, and Seyedali Mirjalili Section II Variants of Moth-Flame Optimization Algorithm Chapter 5 ◾ Multi-objective Moth-Flame Optimization Algorithm for Engineering Problems Nima Khodadadi, Seyed Mohamm ad Mirjalili, and Seyedali Mirjalili Chapter 6 ◾ Accelerating Optimization Using Vectorized Moth-Flame Optimizer (vMFO) AmirPouya Hemm asian, Kazem Meidani, Seyedali Mirjalili, and Amir Barati Farimani Chapter 7 ◾ A Modified Moth-Flame Optimization Algorithm for Image Segmentation Sanjoy Chakraborty, Sukanta Nama, Apu Kumar Saha, and Seyedali Mirjalili Chapter 8 ◾ Moth-Flame Optimization-Based Deep Feature Selection for Cardiovascular Disease Detection Using ECG Signal Arindam Majee, Shreya Bisw as, Somnath Chatterjee, Shibaprasad Sen, Seyedali Mirjalili, and Ram Sarkar Section III Hybrids and Improvements of Moth-Flame Optimization Algorithm Chapter 9 ◾ Hybrid Moth-Flame Optimization Algorithm with Slime Mold Algorithm for Global Optimization Sukanta Nama, Sanjoy Chakraborty, Apu Kumar Saha, and Seyedali Mirjalili Chapter 10 ◾ Hybrid Aquila Optimizer with Moth-Flame Optimization Algorithm for Global Optimization Laith Abualigah, Seyedali Mirjalili, Mohamed Abd Elaziz, Heming Jia, Canan Batur Şahin, Ala’ Khalifeh, and Amir H. Gandomi Chapter 11 ◾ Boosting Moth-Flame Optimization Algorithm by Arithmetic Optimization Algorithm for Data Clustering Laith Abualigah, Seyedali Mirjalili, Mohamm ed Otair, Putra Sumari, Mohamed Abd Elaziz, Heming Jia, and Amir H. Gandomi Section IV Applications of Moth-Flame Optimization Algorithm Chapter 12 ◾ Moth-Flame Optimization Algorithm, Arithmetic Optimization Algorithm, Aquila Optimizer, Gray Wolf Optimizer, and Sine Cosine Algorithm: A Comparative Analysis Using Multilevel Thresholding Image Segmentation Problems Laith Abualigah, Nada Khalil Al-Okbi, Seyedali Mirjalili, Mohamm ad Alshinwan, Husam Al Hamad, Ahmad M. Khasawneh, Waheeb Abu-Ulbeh, Mohamed Abd Elaziz, Heming Jia, and Amir H. Gandomi Chapter 13 ◾ Optimal Design of Truss Structures with Continuous Variable Using Moth-Flame Optimization Nima Khodadadi, Seyed Mohamm ad Mirjalili, and Seyedali Mirjalili Chapter 14 ◾ Deep Feature Selection Using Moth-Flame Optimization for Facial Expression Recognition from Thermal Images Ankan Bhattacharyya, Soumyajit Saha, Shibaprasad Sen, Seyedali Mirjalili, and Ram Sarkar Chapter 15 ◾ Design Optimization of Photonic Crystal Filter Using Moth-Flame Optimization Algorithm Seyed Mohamm ad Mirjalili, Somayeh Davar, Nima Khodadadi, and Seyedali Mirjalili


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Product Details
  • ISBN-13: 9781032070926
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Height: 234 mm
  • No of Pages: 332
  • Width: 156 mm
  • ISBN-10: 1032070927
  • Publisher Date: 13 Mar 2025
  • Binding: Paperback
  • Language: English
  • Sub Title: Variants, Hybrids, Improvements, and Applications


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