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An improved sine cosine water wave optimization algorithm for global optimization

机译:一种改进的全局优化正弦余弦水波优化算法

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摘要

Thewaterwave optimization (WWO) algorithm inspired by shallowwaterwave theory, which has the disadvantages of falling easily into local optimal solution and slower convergence speed and lower calculation accuracy. Concerning this issue, an improved sine cosineWWO algorithm (SCWWO) used elite opposition-based is proposed and to solve optimization functions and structure engineering design problems. First of all, WWO algorithm is combined with the sine cosine algorithm (SCA) in parallel to wave propagation and breaking, because water wave waveform and sine and cosine curves are extremely similar and the SCA algorithm has strong global search capability to improve WWO algorithm's exploitation and exploration capabilities. Secondly, the elite opposition-based learning strategy is introduced into the wave refraction operation that increases the diversity of the population and enhances the exploration capability of WWO algorithm. The SCWWO algorithm clearly improves convergence speed and calculation accuracy. The SCWWO algorithm is compared using 9 benchmark functions. The experimental results demonstrate the feasibility and efficiency of the proposed SCWWO algorithm.
机译:浅层波理论启发的水域优化(WWO)算法,具有易于落入局部最佳解决方案和较慢的收敛速度和较低的计算精度的缺点。关于这个问题,提出了一种改进的正弦舒环赛量算法(SCWWO)的精英基于基于的基于精英反对派,并解决了优化功能和结构工程设计问题。首先,WWO算法与正弦余弦算法(SCA)并联与波传播和断开,因为水波波形和正弦和余弦曲线非常相似,SCA算法具有强大的全球搜索能力,以提高WWO算法的剥削和探索能力。其次,将精英基于反对的学习策略引入了增加人口的多样性并提高了WWO算法的勘探能力。 SCWWO算法显然提高了收敛速度和计算精度。使用9个基准功能进行比较SCWWO算法。实验结果表明了所提出的SCKE算法的可行性和效率。

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