This directory contains scripts to replicate the experiments and the best solutions subdirectory contains the overall best schedules found for each dataset.
Note that, to run the experiments using make, you should first execute make setup in the parent directory first. This command sets up the environment and installs all necessary dependencies.
Each algorithm is run with 10 times with different fixed seeds.
Be aware that running make all would take a very long time and you don't want to do this. Instead, you want to split the runs into individual steps like a specific algorithm on a specific dataset, e.g. make run_e_ga. Below is a list of available commands:
| command | description |
|---|---|
make test |
run a simple sanity check experiment |
make init_experiment |
run a quick experiment comparing different initialization methods |
make run_{b,c,d,e,f}_{ga,hc,sa} |
run a specific algorithm on a specific dataset (using 10 runs with different fixed seeds) |
make run_{b,c,d,e,f} |
run all algorithms on a specific dataset |
make plot_{b,c,d,e,f} |
plot the results of a specific dataset |
make plots |
plot all datasets |
make all |
run everything and plot all results |
If interested in specific parameters of the algorithms, or want to change some settings for the experiments, inspect the Makefile file in this directory.
init_experiment.py- run a quick experiment comparing different initialization methods and generate PDF plots of the resultsoptimize_experiment.py- run a specific algorithm on a specific dataset 10 times with different fixed seedsplot_experiment.py- generate a PDF summarizing the results of all algorithms on a specific dataset