Experimental Data for the preprint "Diagonal Partitioning Strategy Using Bisection of Rectangles and a Novel Sampling Scheme"

This data is used as the basis for the following preprint: N. Guessoum et al. "Diagonal Partitioning Strategy Using Bisection of Rectangles and a Novel Sampling Scheme". Here we experimentally investigated a modification suggested to the recently introduced BIRECT (BIsection of RECTangles) algorithm. A new deterministic approach, named BIRECT-V algorithm (where V stands for vertices), combines bisection with sampling on diagonal vertices. Also, a new variation of the BIRECT-V algorithm, called BIRECT-Vl is also introduced. This data set contains the results of these experiments, the original source codes for the BIRECT-V algorithm used in the experiments, as well as the scripts used for evaluating the results would be available in a future version.
First, We applied both algorithms to several well-known test problems using from the literature, obtaining data1, data4, and data6. Second, we modified the optimization domain for certain functions, and obtained dataset 2, 3, and 5. These results were compared to the original BIRECT, BIRECT-l, DIRECT, and DIRECT-l.

本数据集作为下述预印本的研究基础：N. Guessoum 等人的《采用矩形二分法的对角划分策略与新型采样方案》(Diagonal Partitioning Strategy Using Bisection of Rectangles and a Novel Sampling Scheme)。本研究针对新近提出的二分矩形算法（BIsection of RECTangles，简称BIRECT）的改进方案开展了实验探究。本文提出一种全新的确定性方法，命名为BIRECT-V算法（其中V代表顶点），该方法将二分法与对角顶点采样相结合。此外，本文还提出了BIRECT-V算法的一种新型变体，命名为BIRECT-Vl。本数据集包含上述实验的全部结果、实验中所用BIRECT-V算法的原始源代码；用于评估实验结果的脚本将于后续版本中发布。
首先，我们将两种算法应用于多篇文献中的经典测试问题，得到了数据集data1、data4与data6。其次，我们针对部分函数修改了优化域，得到了数据集2、3与5。我们将上述实验结果与原始BIRECT、BIRECT-l、DIRECT及DIRECT-l进行了对比。