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Spotted Hyena Optimizer for Solving Engineering Design Problems

机译:斑点鬣狗优化器解决工程设计问题

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This paper presents a recently developed metaheuristic optimization algorithm named as Spotted Hyena Optimizer (SHO) which is inspired by the social behaviors of spotted hyenas. The three basic steps of SHO are searching for prey, encircling, and attacking prey which are mathematically modeled and discussed. The main concept of this work is to applied the SHO algorithm on two very challenging real-life constrained engineering design problems (i.e., 25-bar truss design and multiple disk clutch brake design) and compared it with other various metaheuristic algorithms. The experimental results of engineering design problems reveal that SHO algorithm performs better than the other competitor metaheuristic algorithms.
机译:本文提出了一种最新开发的元启发式优化算法,称为斑点鬣狗优化程序(SHO),该算法受斑点鬣狗的社会行为的启发。 SHO的三个基本步骤是搜索猎物,包围猎物和攻击猎物,并对其进行数学建模和讨论。这项工作的主要概念是将SHO算法应用于两个非常具有挑战性的,现实生活中受约束的工程设计问题(即25巴桁架设计和多盘离合器制动器设计),并将其与其他各种元启发式算法进行比较。工程设计问题的实验结果表明,SHO算法的性能优于其他竞争对手的元启发式算法。

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