Название: Structural Optimization Using Shuffled Shepherd Meta-Heuristic Algorithm: Extensions and ApplicationsАвтор: Ali Kaveh, Ataollah Zaerreza
Издательство: Springer
Серия: Studies in Systems, Decision and Control
Год: 2023
Страниц: 288
Язык: английский
Формат: pdf (true)
Размер: 12.2 MB
This book presents the so-called Shuffled Shepherd Optimization Algorithm (SSOA), a recently developed meta-heuristic algorithm by authors. There is always limitations on the resources to be used in the construction. Some of the resources used in the buildings are also detrimental to the environment. For example, the cement utilized in making concrete emits carbon dioxide, which contributes to the global warming. Hence, the engineers should employ resources efficiently and avoid the waste. In the traditional optimal design methods, the number of trials and errors used by the designer is limited, so there is no guarantee that the optimal design can be found for structures. Hence, the deigning method should be changed, and the computational algorithms should be employed in the optimum design problems. The four primary categories of metaheuristic algorithms are evolution-based, physics-based, swarm-based, and human-based, depending on their inspiration. Evolutionary algorithms are inspired by the characteristics of the biological evolution, including crossover, mutation, and selection. Inspiration of swarm intelligence algorithms is based on the social behavior of creatures living in a group, which might be a swarm, herd, or flock. The human-based algorithms consist of optimizers that simulate certain human behaviors. As the fourth class of metaheuristic algorithms, physics-based algorithms are motivated by physical rules.
