Spotted hyena optimizer: A novel bio-inspired based metaheuristic technique for engineering applications

By Gaurav Dhiman, Vijay Kumar. Advances in Engineering Software, 2017

956 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/da3f8bc8a11242de8e5497e33641e333cda3719e

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Citations in the corpus

An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges (2023, background): “(2012) 1 3 Table 1 (continued) SN Algorithm References 49 Asexual Reproduction Optimization (ARO) Farasat et al.”
Metaheuristic Algorithms on Feature Selection: A Survey of One Decade of Research (2009-2019) (2021, methodology): “optimization algorithm [67], animal migration optimization [69], shark smell optimization [70], spotted hyena optimizer [84], emperor penguins colony [88].”
Salp swarm algorithm: a comprehensive survey (2019, methodology): “…algo-rithm [23], bacterial foraging algorithm [24], biogeogra-phy-based optimization [25], gray wolf optimizer (GWO) algorithm [26], ant lion optimization [27], particle swarm optimization algorithm [28], spotted hyena optimizer algorithm [29], and other related studies found in [1, 17] (see Fig.”
Support vector regression optimized by meta-heuristic algorithms for daily streamflow prediction (2020, methodology): “More details about using the SHO algorithm, readers are referred to (Dhiman and Kumar 2017, 2018).”
A novel algorithm for global optimization: Rat Swarm Optimizer (2020, background): “2009), Cuckoo Search (CS) (Yang and Deb 2009), Firefly Algorithm (FA) (Yang 2010a), Batinspired Algorithm (BA) (Yang 2010b), Spotted Hyena Optimizer (SHO) (Dhiman and Kumar 2017), and Hunting Search (HUS) (Oftadeh et al.”
STOA: A bio-inspired based optimization algorithm for industrial engineering problems (2019, background): “Most of the real world problems (Chandrawat et al., 2017; Singh and Dhiman, 2017; Kaur and Dhiman, 2019; Singh and Dhiman, 2018b; Singh et al., 2018b,a; Kaur et al., 2018; Dhiman et al., 2018, 2019; Dhiman and Kumar, 2018) have high computational cost, nonlinear constraints, non-convex, and huge…”
Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems (2019, methodology): “For F5 test function, SHO and GWO are the second and third best optimization algorithm.”