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Performance analysis of Chaotic Multi-Verse Harris Hawks Optimization: A case study on solving engineering problems

机译:混沌多诗Harris Hawks优化的性能分析:以解决工程问题为例

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摘要

In recent years, several optimization algorithms are proposed, one of them is Multi-Verse Optimizer (MVO). In this paper, a modified version of MVO is proposed, called CMVHHO, which uses the chaos theory and the Harris Hawks Optimization (HHO). The main aim of using the chaotic maps in the proposed method is to determine the optimal value for the parameters of the basic MVO. Besides, the HHO is used as a local search to improve the ability of the MVO to exploit the search space. The performance of the CMVHHO is conducted using a set of chaotic maps to determine the most suitable map, as well as, the different experiments are performed to determine which parameter has the largest effect on the effectiveness of the MVO. Moreover, the performance of the CMVHHO is compared with a set of state-of-the-art algorithms to find the best solution for global optimization problems. Furthermore, the proposed CMVHHO with the best map is applied to solve four well-known engineering problems. The experimental results illustrate that the chaotic Circle map is the best map among all maps because it improved the performance of the CMVHHO, as well as the HHO, affected positively in the behavior of the proposed algorithm. The CMVHHO showed the best results than other algorithms in terms of the performance measures as well as in engineering problems and it outperformed the state-of-the-art algorithms in all problems.
机译:近年来,提出了几种优化算法,其中之一是多版本优化器(MVO)。在本文中,提出了MVO的改进版本,称为CMVHHO​​,它使用了混沌理论和哈里斯·霍克斯优化(HHO)。在该方法中使用混沌映射的主要目的是确定基本MVO参数的最佳值。此外,HHO用作本地搜索,以提高MVO利用搜索空间的能力。使用一组混沌图来确定最合适的图,从而执行CMVHHO​​的性能,并执行不同的实验以确定哪个参数对MVO的效果影响最大。此外,将CMVHHO​​的性能与一组最新算法进行了比较,以找到针对全局优化问题的最佳解决方案。此外,将所提出的具有最佳映射的CMVHHO​​用于解决四个众所周知的工程问题。实验结果表明,混沌圆图是所有图中最好的图,因为它改善了CMVHHO​​以及HHO的性能,并对该算法的行为产生了积极影响。在性能指标以及工程问题方面,CMVHHO​​表现出优于其他算法的最佳结果,并且在所有问题上均优于最新算法。

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