Structural Optimization Using Shuffled Shepherd Meta-Heuristic Algorithm Structural Optimization Using Shuffled Shepherd Meta-Heuristic Algorithm
Studies in Systems, Decision and Control

Structural Optimization Using Shuffled Shepherd Meta-Heuristic Algorithm

Extensions and Applications

    • USD 139.99
    • USD 139.99

Descripción editorial

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 gradient-based method and meta-heuristic algorithms are the two different types of methods used to find the optimal solution. The gradient-based methods require gradientinformation. Also, these can easily be trapped in the local optima in the nonlinear and complex problems. Therefore, to overcome these issues, meta-heuristic algorithms are developed. These algorithms are simple and can get out of the local optimum by easy means. However, a single meta-heuristic algorithm cannot find the optimum results in all types of optimization problems. Thus, civil engineers develop different meta-heuristic algorithms for their optimization problems.


Different applications of the SSOA are provided. The simplified and enhanced versions of the SSOA are also developed and efficiently applied to various optimization problems in structures. Another special feature of this book consists of the use of graph theoretical force method as analysis tool, in place of traditional displacement approach. This has reduced the computational time to a great extent, especially for those structures having smaller DSI compared to the DKI. New framework is also developed for reliability-based design of frame structures. The algorithms are clearly stated such that they can simply be implemented and utilized in practice and research.

GÉNERO
Técnicos y profesionales
PUBLICADO
2023
1 de marzo
IDIOMA
EN
Inglés
EXTENSIÓN
292
Páginas
EDITORIAL
Springer Nature Switzerland
VENDEDOR
Springer Nature B.V.
TAMAÑO
75.8
MB
Applications of Artificial Neural Networks and Machine Learning in Civil Engineering Applications of Artificial Neural Networks and Machine Learning in Civil Engineering
2024
Chaotic Meta-heuristic Algorithms for Optimal Design of Structures Chaotic Meta-heuristic Algorithms for Optimal Design of Structures
2024
Topological Transformations for Efficient Structural Analysis Topological Transformations for Efficient Structural Analysis
2022
Advanced Metaheuristic Algorithms and Their Applications in Structural Optimization Advanced Metaheuristic Algorithms and Their Applications in Structural Optimization
2022
Advances in Metaheuristic Algorithms for Optimal Design of Structures Advances in Metaheuristic Algorithms for Optimal Design of Structures
2021
Swift Analysis of Civil Engineering Structures Using Graph Theory Methods Swift Analysis of Civil Engineering Structures Using Graph Theory Methods
2020
Systems, Decision and Control in Energy IV Systems, Decision and Control in Energy IV
2023
Control Synthesis for Semi-Markovian Switching Systems Control Synthesis for Semi-Markovian Switching Systems
2023
Error Logic: Paving Pathways for Intelligent Error Identification and Management Error Logic: Paving Pathways for Intelligent Error Identification and Management
2023
Group Verbal Decision Analysis Group Verbal Decision Analysis
2023
Developments in Information and Knowledge Management Systems for Business Applications Developments in Information and Knowledge Management Systems for Business Applications
2023
Decision Making Under Uncertainty, with a Special Emphasis on Geosciences and Education Decision Making Under Uncertainty, with a Special Emphasis on Geosciences and Education
2023