Data for "Optimal Static Mutation Strength Distributions for the (1+λ) Evolutionary Algorithm on OneMax"

This collection contains the data (and the copy of the code that generated that data) for the paper "Optimal Static Mutation Strength Distributions for the (1+λ) Evolutionary Algorithm on OneMax" accepted for the GECCO 2021 conference. The files are: one-plus-lambda-on-onemax.tar.gz: the source code to reproduce the experiments. algorithm-expectations-flat.csv: the expected running times of various \((1+\lambda)\) algorithms, including the one that uses optimal distributions. static-N-distributions.csv: the distributions optimized by CMA-ES, where N is the problem size. static-N-distribution-stddev.csv: maximum deviation between the distributions over the "accepted" runs. static-N-deviations.csv: the sorted deviations of the outcomes of distribution optimization compared to the best achieved runs. static-N-summary.csv: the expected running times of the \((1+\lambda)\) EA using the optimal distribution. static-N-fitness-log.csv: fitness traces from the optimization runs.本数据集收录了已被2021年国际遗传与进化计算大会（GECCO 2021）收录的论文《(1+λ)进化算法在OneMax问题上的最优静态突变强度分布》相关的数据，以及生成该数据集的代码副本。所包含的文件如下： 1. one-plus-lambda-onemax.tar.gz：用于复现实验的源代码； 2. algorithm-expectations-flat.csv：各类(1+λ)进化算法的期望运行时间，其中包含采用最优分布的算法； 3. static-N-distributions.csv：由协方差矩阵自适应进化策略（Covariance Matrix Adaptation Evolution Strategy，CMA-ES）优化得到的分布，其中N为问题规模； 4. static-N-distribution-stddev.csv：合规运行批次中各分布间的最大偏差值； 5. static-N-deviations.csv：分布优化结果与最优运行结果之间偏差的排序后数据集； 6. static-N-summary.csv：采用最优分布的(1+λ)进化算法的期望运行时间； 7. static-N-fitness-log.csv：优化运行过程中的适应度轨迹数据。