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Spotted Hyena Optimizer for Solving Complex and Non-linear Constrained Engineering Problems

机译:察觉鬣狗优化器解决复杂和非线性约束工程问题

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This paper presents a metaheuristic optimization algorithm named as Spotted Hyena Optimizer (SHO) for solving complex and nonlinear constrained engineering problems. The fundamental concept of this algorithm is the hunting strategy of spotted hyena in nature. The three basic steps of proposed SHO algorithm are searching, encircling, and attacking for prey. The proposed SHO algorithm is applied to two real-life complex and nonlinear constrained engineering problems to ensure its applicability in high-dimensional environment. The experimental results of engineering problems reveal that SHO algorithm outperforms other competitive approaches.
机译:本文介绍了一个名为斑点鬣狗优化器(SHO)的成群质优化算法,用于解决复杂和非线性约束工程问题。该算法的基本概念是斑点鬣狗本质上的狩猎策略。提出的Sho算法的三个基本步骤正在搜索,环绕和攻击猎物。所提出的Sho算法应用于两个现实寿命和非线性约束工程问题,以确保其在高维环境中的适用性。工程问题的实验结果表明,Sho算法优于其他竞争方法。

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