Data Sets for the study "What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms"

<p>This is the dataset of the paper "What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms"</p> <ul> <li>figures.ipynb&nbsp;provides postprocessing codes for using the attached data to generate&nbsp;tables and figures in the paper.</li> <li>the csv folder consists of the raw data of function evaluations that algorithms used to hit each solution the first time.</li> <li>the metric folder consists of the processed data, which records the convergence&nbsp;process of two single objectives (y1 and y2), Hypervolume, and the number of obtained Pareto solutions.</li> <li>the gif folder&nbsp;consists&nbsp;of the gif files plotting the convergence process of solving LOTZ.</li> </ul> <p>&nbsp;</p> <p>The code used to generate this data is available at https://github.com/FurongYe/GSEMO</p>