Multi-threaded Spotted Hyena Optimizer with thread-crossing techniques

This paper presents a Multi-threaded version of the Spotted Hyena Optimizer algorithm with thread-crossing techniques (MT-SHO) to improve the ability of the algorithm to explore the search space. The original algorithm is inspired by the hunting behavior of the spotted hyena. Along the different sec...

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Bibliographic Details
Published in:Procedia computer science Vol. 179; pp. 432 - 439
Main Authors: Martinez-Rios, Felix, Murillo-Suarez, Alfonso
Format: Journal Article
Language:English
Published: Elsevier B.V 2021
Subjects:
Genetic algorithms
Global optimization
Metaheuristic
Multi-threaded algorithms
Nature-inspired algorithms
Simulated annealing
Spotted Hyena Optimizer
Metaheuristic
Global optimization
Multi-threaded algorithms
Nature-inspired algorithms
Simulated annealing
Spotted Hyena Optimizer
Genetic algorithms
ISSN:1877-0509, 1877-0509
Online Access:Get full text
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Summary:This paper presents a Multi-threaded version of the Spotted Hyena Optimizer algorithm with thread-crossing techniques (MT-SHO) to improve the ability of the algorithm to explore the search space. The original algorithm is inspired by the hunting behavior of the spotted hyena. Along the different sections of the work, we explain in detail how the original algorithm simulates the spotted hyena’s behavior to optimize highly complex mathematical functions and how we handle the procedures and results of the multi-threaded version, with thread-crossing techniques that improve the ability to explore and exploit the search space by letting threads learn between them. We present the experiments used to determine the best value of the parameters used in the parallel version of the algorithm and to prove that our proposal obtains significantly good results we compare the results obtained by evaluating 24 benchmark functions with the results published for the original algorithm as well as other metaheuristic algorithms.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2021.01.026