论文标题
全局优化的新硬基准功能
New hard benchmark functions for global optimization
论文作者
论文摘要
在本文中，我们提出了一些新的单峰，多模式和噪声测试功能，以评估全局优化算法的性能。所有测试功能都是多维问题。拟议功能的2维景观已在3D空间中图形化表示，以显示它们的几何形状，但是这些功能在大于3的维度上更为复杂。为了显示这些功能的硬度，我们已经通过一些强大的算法进行了一项实验性研究，例如CEC竞争者，例如CEC竞争者：LSHADE，MADDE，MADDE，LSHDE和LSHADE-SPAC-SPACMA AlgorithMS。除了新型算法外，切线搜索算法（TSA）及其改进的切线搜索算法（MTSA）也用于实验研究中。发现的结果证明了所提出的功能的硬度。建议的测试功能的代码源可在MATLAB Exchange网站上获得。 https://www.mathworks.com/matlabcentral/fileexchange/106450-new-hard-benchmark-functions-for-global-optimization？s_tid=srchtitle
In this paper, we present some new unimodal, multimodal, and noise test functions to assess the performance of global optimization algorithms. All the test functions are multidimensional problems. The 2-dimension landscape of the proposed functions has been graphically presented in 3D space to show their geometry, however these functions are more complicated in dimensions greater than 3. To show the hardness of these functions, we have made an experimental study with some powerful algorithms such as CEC competition winners: LSHADE, MadDe, and LSHADE-SPACMA algorithms. Besides the novel algorithm, Tangent search algorithm (TSA) and its modified Tangent search algorithm (mTSA) were also used in the experimental study. The results found demonstrate the hardness of the proposed functions. The code sources of the proposed test functions are available on Matlab Exchange website. https://www.mathworks.com/matlabcentral/fileexchange/106450-new-hard-benchmark-functions-for-global-optimization?s_tid=srchtitle
