Название: Advanced Metaheuristic Algorithms and Their Applications in Structural OptimizationАвтор: Ali Kaveh, Kiarash Biabani Hamedani
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2022
Страниц: 369
Язык: английский
Формат: pdf (true)
Размер: 17.1 MB
The main purpose of the present book is to develop a general framework for population-based metaheuristics based on some basic concepts of set theory. The idea of the framework is to divide the population of individuals into subpopulations of identical sizes. Therefore, in each iteration of the search process, different subpopulations explore the search space independently but simultaneously. The framework aims to provide a suitable balance between exploration and exploitation during the search process. A few chapters containing algorithm-specific modifications of some state-of-the-art metaheuristics are also included to further enrich the book.
Chapter 1 explains the purpose of the book and provides an overview of the remaining chapters. In Chap. 2, the set-theoretical shuffled shepherd optimization algorithm is introduced and applied to the optimal design of reinforced concrete cantilever retaining walls. Chapter 3 introduces the set-theoretical variants of the teaching-learning-based optimization algorithm for structural optimization with frequency constraints. In Chap. 4, enhanced versions of the shuffled shepherd optimization algorithm are developed for structural optimization. In Chap 5, a number of set-theoretical metaheuristic algorithms are applied to reliability-based design optimization of truss structures. In Chap. 6, optimal analysis is used in the service of frequency-constrained optimization of cyclic symmetric structures with set-theoretical Jaya algorithm. Discrete structural optimization with set-theoretical Jaya algorithm is discussed in Chap. 7. In Chap. 8, enhanced forensic-based investigation algorithm is introduced and its application to structural optimization with frequency constraints is examined. In Chap. 9, improved slime mould algorithm is developed for structural optimization with frequency constraints. Finally, in Chap. 10, improved arithmetic optimization algorithm is proposed for discrete structural optimization.
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