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Erschienen in:
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2023 | OriginalPaper | Buchkapitel

2. Shuffled Shepherd Optimization Method: A New Meta-Heuristic Algorithm

verfasst von : Ali Kaveh, Ataollah Zaerreza

Erschienen in: Structural Optimization Using Shuffled Shepherd Meta-Heuristic Algorithm

Verlag: Springer Nature Switzerland

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Excerpt

This chapter introduces a recently established multi-community metaheuristic optimization algorithm introduced by Kaveh and Zaerreza [1]. This algorithm is known as shuffled shepherd optimization algorithm (SSOA), in which the agents are first divided into multi-communities. Then the optimization procedure inspired from the behavior of a shepherd in nature is performed, on each community. The SSOA is tested on 17 mathematical benchmark optimization problems, 2 classic engineering problems, 5 truss design problems, and one double-layer grid design problem. The results demonstrate that SSOA is competitive with other considered metaheuristic algorithms. …

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Vorheriges Kapitel Introduction
Nächstes Kapitel Shuffled Shepherd Optimization Method Simplified for Reducing the Parameter Dependency
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Metadaten
Titel
Shuffled Shepherd Optimization Method: A New Meta-Heuristic Algorithm
verfasst von
Ali Kaveh
Ataollah Zaerreza
Copyright-Jahr
2023
Buch
Structural Optimization Using Shuffled Shepherd Meta-Heuristic Algorithm

Print ISBN: 978-3-031-25572-4

Electronic ISBN: 978-3-031-25573-1

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-3-031-25573-1_2