Biologically_Inspired_Algorithms

Repository for biologically inspired algorithms classes.

How to run the experiments:

1. Build the main program
   g++ -o bio_alg main.cpp random.cpp Problem.cpp solution.cpp utils.cpp -std=c++17

2. Create a batch script for running the runtime evaluations e.g.:
   python .\create_batch.py data/qap/ results/runtime_results.txt p.txt batch_files/run_runtime.bat --mode runtime

3. Run the runtime evaluation batch script e.g.:
   .\batch_files/run_runtime.bat

4. Copy the mean runtime of greedyLS algorithm for each instance into create_batch.py

5. Create a batch script for running the performance evaluations e.g.:
   python .\create_batch.py data/qap/ r.txt results/performance_results.txt batch_files/run_performance.bat --mode performance

6. Run the performance evaluation batch script e.g.:
   .\batch_files/run_performance.bat

7. Create batch script for running the MSLS number of restarts evaluations e.g.:
   python .\create_batch.py data/qap/ r.txt results/MSLS_restarts_results.txt batch_files/run_msls_performance.bat --mode performance_restarts

8. Run the MSLS number of restarts evaluations batch script e.g.:
   .\batch_files/run_msls_performance.bat

9. Visualize results with LS_Results.ipynb (remember to set appropriate paths to result files)