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A novel paddy field algorithm based on pattern search method

机译:基于模式搜索的稻田算法

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Paddy field algorithm (PFA) is a fast random algorithm with global search capability. But when the number of solutions is over the range, the algorithm efficiency becomes low because it executes a lot of redundant iterations. Pattern search algorithm is sensitive to the initial condition. In order to strength the local search ability, paddy field algorithm is introduced and a novel paddy field algorithm is proposed in this paper. The hybrid algorithm operates by initially scattering seeds at random in the parameter space. The final result is found by pattern search based on the result of PFA algorithm. This algorithm is tested on three sample functions alongside the basic paddy field algorithm and pattern search method. The simulation results show that the algorithm performs well.
机译:稻田算法(PFA)是一种具有全局搜索功能的快速随机算法。但是,当解决方案的数量超出范围时,由于执行大量的冗余迭代,算法效率会降低。模式搜索算法对初始条件敏感。为了增强局部搜索能力,介绍了稻田算法,提出了一种新颖的稻田算法。混合算法通过首先在参数空间中随机散布种子来进行操作。根据PFA算法的结果,通过模式搜索找到最终结果。除基本的稻田算法和模式搜索方法外,还对三个示例函数测试了该算法。仿真结果表明该算法性能良好。

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