Code to reproduce the experiments from: Optimizing Genetic Algorithms Using the Binomial Distribution
Copyright © 2023-2024 Vincent A. Cicirello
This repository contains code to reproduce the experiments, and analysis of experimental data, from the following paper:
Vincent A. Cicirello. 2024. Optimizing Genetic Algorithms Using the Binomial Distribution. Proceedings of the 16th International Joint Conference on Computational Intelligence, pages 159-169. November 2024. doi:10.5220/0013038300003837.
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The experiments depend upon the following libraries, which are automatically downloaded from Maven Central during the build process:
- Chips-n-Salsa 7.0.0
- JavaPermutationTools 6.0.0
- ρμ 4.1.0
- org.cicirello.core 2.7.0
To build and run the experiments on your own machine, you will need the following:
- JDK 17: I used OpenJDK 17, but other distributions should be fine.
- Apache Maven: In the root of the repository, there is a
pom.xml
for building the Java programs for the experiments. Using thispom.xml
, Maven will take care of downloading the exact version of Chips-n-Salsa (release 7.0.0) and its dependencies that were used in the experiments. - Python 3: The repository contains Python programs that were used to process the raw data for the paper. If you want to run the Python programs, you will need Python 3.
- Make: The repository contains a Makefile to simplify running the build, running the experiment's Java programs, and running the Python program to analyze the data. If you are familiar with using the Maven build tool, and running Python programs, then you can just run these directly, although the Makefile may be useful to see the specific commands needed.
The source code of the Java programs implementing the experiments is in the src/main/java directory. You can build the experiment programs in one of the following ways.
Using Maven: Execute the following from the root of the repository.
mvn clean package
Using Make: Or, you can execute the following from the root of the repository.
make build
If you just want to inspect the data from my runs, then you can find that output in the /data directory. If you instead want to run the experiments yourself, you must first follow the build instructions. Once the jar of the experiments is built, you can then run the experiments with the following executed at the root of the repository:
make experiments
If you don't want to overwrite my original data files, then first change the variable
pathToDataFiles
in the Makefile
before running the above command.
To run the Python programs that process the raw data and generate the figures from the paper, you need Python 3 installed. The source code of the Python programs is found in the src/analysis directory. To run the analysis, execute the following at the root of the repository:
make figures
This make command will also take care of installing any required Python packages if you don't already have them installed.
If you want to generate the figures in pdf
format, then after executing the
above, proceed to execute the following (which assumes that you have epstopdf
installed):
make epstopdf
If you don't want to overwrite my original data files, and figures, then change the
variable pathToDataFiles
in the Makefile
before running the above commands.
There are other files, potentially of interest, in the repository, including:
system-stats.txt
: This file contains details of the system I used to run the experiments, such as operating system, processor specs, Java JDK and VM. It is in the /data directory.
The code to replicate the experiments from the paper, as well as the Chips-n-Salsa library and its dependencies, are licensed under the GNU General Public License 3.0.