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Hybrid bat algorithm and direct search methods for solving minimax problems

机译:混合蝙蝠算法和直接搜索方法求解极大极小问题

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摘要

The aim of this paper is to produce a new hybrid algorithm to solve minimax problems by combining the bat algorithm with direct search methods. The proposed algorithm is called hybrid bat direct search algorithm (HBATDS). In HBATDS, the global exploration and the local exploitation process are balanced. The bat algorithm has a good ability to make exploration and exploitation search. The exploitation capability of the proposed algorithm is increased by invoking the pattern search method as a local search method instead of the random walk method in the standard bat algorithm. In the final stage of the algorithm, the Nelder-Mead method is applied in order to refine the best found solution from the bat and pattern search method instead of running the algorithm more iterations without any improvements in the fitness function value. The performance of the HBATDS algorithm is investigated by applying it on 10 minimax problems and comparing it against 8 benchmark algorithms. The experimental results indicate that HBATDS is a promising algorithm and outperforms the other algorithms in most cases.
机译:本文的目的是通过将蝙蝠算法与直接搜索方法相结合,产生一种新的混合算法来解决极大极小问题。所提出的算法称为混合蝙蝠直接搜索算法(HBATDS)。在HBATDS中,全球勘探和本地开采过程是平衡的。 bat算法具有很好的进行探索和利用搜索的能力。通过将模式搜索方法(而不是标准bat算法中的随机游走方法)用作局部搜索方法,从而提高了该算法的开发能力。在算法的最后阶段,应用Nelder-Mead方法是为了从蝙蝠和模式搜索方法中优化找到的最佳解决方案,而不是在不对适应度函数值进行任何改进的情况下对算法进行更多的迭代。通过将HBATDS算法应用于10个minimax问题并将其与8个基准算法进行比较,研究了HBATDS算法的性能。实验结果表明,HBATDS是一种很有前途的算法,在大多数情况下都优于其他算法。

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