Copyright © 2023 Vincent A. Cicirello

This repository contains code to reproduce the experiments, and analysis of experimental data, from the following paper:

Vincent A. Cicirello. 2023. A Survey and Analysis of Evolutionary Operators for Permutations. In Proceedings of the 15th International Joint Conference on Computational Intelligence, pages 288-299. doi:10.5220/0012204900003595.

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Packages and Releases

The experiments depend upon the following libraries, and in some cases this research has also contributed to these libraries:

• Chips-n-Salsa
• JavaPermutationTools

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 this pom.xml, Maven will take care of downloading the exact version of Chips-n-Salsa (release 6.4.0) 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

As an alternative to building the jar (see above), you can choose to instead download a prebuilt jar of the experiments from the Maven Central repository. The Makefile contains a target that will do this for you, provided that you have curl installed on your system. To download the jar of the precompiled code of the experiments, run the following from the root of the repository:

make download

The jar that it downloads contains the compiled code of the experiments as well as all dependencies within a single jar file.

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 either follow the build instructions or download a prebuilt jar (see above sections). Once the jar of the experiments is either built or downloaded, 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 program that I used to process the raw data,
and generate the figures for the paper, you need Python 3 installed. The source code of the Python programs is found in the src/main/python directory. To run the analysis, execute the following at the root of the repository:

make analysis

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 command.

This will analyze the data from the /data directory. It will also generate the figures, etc in that directory. This make command will also take care of installing any required Python packages if you don't already have them installed.

There are a few other files, potentially of interest, in the repository, which include:

• 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 is licensed under the GNU General Public License 3.0.