DOI: 10.5281/zenodo.5567725
title: Experimental Data for the Paper "Frequency Fitness Assignment: Optimization without a Bias for Good Solutions can be Efficient"

description: <strong><em>The data for the paper "Frequency Fitness Assignment: Optimization without a Bias for Good Solutions can be Efficient"</em></strong> This is the data set with the experimental results for our paper "Frequency Fitness Assignment: Optimization without a Bias for Good Solutions can be Efficient." We conduct more than 56 million runs, consuming more than 6.5*10<sup>14</sup> FEs as well as 150 processor years, ensuring that our results are statistically sound and rigorous. Here, you can find all the results, all the program codes used for obtaining the results, and all the tables and figures produced from the results, and the program codes used to produce them. <strong><em>Included Files</em></strong> <code>ffa-empirical-complexity_results.tar.xz</code> (size packed 11.7 GiB, unpacked 335.2 GiB): The complete set of log files. For each run of each experiment, one distinct text-based log file is created. The log file contains every improving step of the algorithm, the final result, and the system configuration. This archive is very large and unpacked it will occupy more than 335 GiB of hard disk space. <code>ffa-empirical-complexity_end_of_run_results_and_stats.tar.xz</code> (size packed 861.4 MiB, unpacked 6,295.9 MiB): The end-of-run result qualities and consumed runtime as well as statistics thereof. These information have been extracted from the log files and are provided in form of semicolon-separated values text files. These files are much easier to consume. They do not reflect the progress of the single runs, but only their end results. <code>ffa-empirical-complexity_sources.tar.xz</code> (size packed 65.5 MiB, unpacked 173.6 MiB): The complete set of <code>Java</code> sources that was used to perform the experiments. Since the random seeds of the random number generators are created in a deterministic way, you could execute this code and obtain the exactly same log files in terms of consumed FEs, improving steps, and end results as we provide in <code>ffa-empirical-complexity_results.tar.xz</code>. (Of course, your systems configuration and measured runtime in milliseconds would probably be different.) <code>ffa-empirical-complexity_evaluator.tar.xz</code> (size packed 4,015.8 KiB, unpacked 4,510 KiB): The <code>Java</code> and <code>R</code> source codes that are used to extract the end results from the log files, compute all relevant statistics, and produce the graphics in our article. <code>ffa-empirical-complexity_evaluation.tar.xz</code> (size packed 417.3 KiB, unpacked 590.0 KiB): The high-level conclusions produced by the evaluator from the raw data, including tables and figures. <code>ffa-empirical-complexity_saga_ffa_on_plateau.tar.xz</code> (size packed 7,238.9 KiB, unpacked 26.8 MiB): We also conducted an additional experiment to better understand the behavior of the SAGA algorithm variants using FFA on the Plateau problem. Here we provide source codes and result log files of this experiment. The result log files are much more comprehensive, as we tried to figure out why these algortihms were able to solve the Plateau problems (and they ultimately helped us to successfully do so). <strong><em>License</em></strong> The copyright holder of this dataset is Prof. Dr. Thomas Weise (see Contact). The dataset is licensed under the Creative Commons Attribution 4.0 International License. <strong><em>Contact</em></strong> If you have any questions or suggestions, please contact the corresponding author of this dataset, Prof. Dr. Thomas Weise of the Institute of Applied Optimization (IAO) at Hefei University [合肥学院] in Hefei, Anhui, China via email to tweise@hfuu.edu.cn with CC to tweise@ustc.edu.cn.