Butterfly Optimization Algorithm: Theory and Engineering Applications

The book discusses the theory and applications of the butterfly optimization algorithm (BOA), hybridization, complexity analysis, constraint handling, and its implementation on real-world problems. It compares the simulated results with other basic algorithms and demonstrates the efficacy of the BOA through statistical analysis.

Format: Paperback / softback
Length: 86 pages
Publication date: 19 July 2022
Publisher: Springer Verlag, Singapore

This book delves into the realm of the recently introduced butterfly optimization algorithm (BOA), presenting both its theoretical foundations and practical applications. It also emphasizes the hybridization process within the basic structure of BOA, conducting a comprehensive analysis of its complexity. Furthermore, it elucidates the constraint handling mechanism employed by BOA. In addition, the book showcases the implementation and validation of a novel variant of BOA on a diverse range of linear and nonlinear real-world problems from the engineering and pulp and paper industries. The simulated outcomes are compared with various basic algorithms, providing a quantitative assessment of the algorithm's effectiveness. Comparative and nonparametric statistical result analysis further substantiates the efficacy of the BOA in solving complex optimization challenges.

Introduction:
The butterfly optimization algorithm (BOA) has gained significant attention in recent years due to its remarkable performance in solving optimization problems. This book aims to provide a comprehensive exploration of BOA, encompassing its theoretical foundations, practical applications, and complexity analysis. By delving into the hybridization process within the basic structure of BOA, the book offers a deep understanding of its workings. Furthermore, it sheds light on the constraint handling mechanism employed by BOA, enabling it to handle complex optimization scenarios effectively.
Theory and Applications:
The book begins by introducing the concept of BOA and its motivation behind its development. It then proceeds to present the theoretical foundations of BOA, including its mathematical formulation, convergence properties, and search strategies. The theoretical aspects are complemented by practical examples and case studies, showcasing the application of BOA in various fields such as machine learning, engineering, and finance.
Hybridization Process:
One of the key features of BOA is its ability to hybridize with other optimization algorithms, enhancing its performance and versatility. The book delves into the hybridization process, exploring how BOA can be combined with other algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), and simulated annealing (SA). The hybridization process is illustrated through practical examples and case studies, demonstrating the benefits of combining BOA with other algorithms.
Complexity Analysis:
Understanding the complexity of BOA is crucial for its practical application. The book conducts a thorough analysis of BOA's complexity, including its time and space complexity. It also discusses the influence of parameters such as population size, mutation rate, and learning rate on the algorithm's performance. The complexity analysis provides insights into the limitations and potential improvements of BOA.
Constraint Handling:
BOA is designed to handle constraints effectively, which are often encountered in real-world optimization problems. The book explores the constraint handling mechanism employed by BOA, including penalty functions, constraint types, and constraint violation detection. It also discusses the strategies used to handle constraints, such as constraint relaxation, constraint tightening, and constraint modification.
Implementation and Validation:
To demonstrate the practicality of BOA, the book showcases the implementation and validation of a novel variant of BOA on a diverse range of linear and nonlinear real-world problems from the engineering and pulp and paper industries. The simulated results are compared with various basic algorithms, providing a quantitative assessment of the algorithm's effectiveness. Comparative and nonparametric statistical result analysis further substantiates the efficacy of the BOA in solving complex optimization challenges.
Conclusion:
In conclusion, this book presents a comprehensive and in-depth exploration of the butterfly optimization algorithm (BOA). It provides a theoretical foundation, practical applications, and a detailed analysis of its complexity. The book also highlights the hybridization process with other optimization algorithms and the constraint handling mechanism employed by BOA. Through implementation and validation on real-world problems, the book demonstrates the efficacy of BOA in solving complex optimization challenges. This book is a valuable resource for researchers, practitioners, and students interested in optimization algorithms and their applications.

Weight: 163g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811937668
Edition number: 1st ed. 2022