Shuffled shepherd optimization method: a new Meta-heuristic algorithm
ISSN: 0264-4401
Article publication date: 11 March 2020
Issue publication date: 18 June 2020
Abstract
Purpose
This paper aims to present a new multi-community meta-heuristic optimization algorithm, which is called shuffled shepherd optimization algorithm (SSOA). In this algorithm.
Design/methodology/approach
The agents are first separated into multi-communities and the optimization process is then performed mimicking the behavior of a shepherd in nature operating on each community.
Findings
A new multi-community meta-heuristic optimization algorithm called a shuffled shepherd optimization algorithm is developed in this paper and applied to some attractive examples.
Originality/value
A new metaheuristic is presented and tested with some classic benchmark problems and some attractive structures are optimized.
Keywords
Acknowledgements
Compliance with ethical standards: Conflict of interest: No potential conflict of interest was reported by the authors.
Citation
Kaveh, A. and Zaerreza, A. (2020), "Shuffled shepherd optimization method: a new Meta-heuristic algorithm", Engineering Computations, Vol. 37 No. 7, pp. 2357-2389. https://doi.org/10.1108/EC-10-2019-0481
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited