This repository contains code for both deterministic EAs where only one crossover operator can be used throughout the whole process, and a probabilistic EA where multiple crossover operators can be adopted with specific probability proportions.
A meta-EA is also implemented to find the best probability proportion scheme of multiple crossovers operators.
- Master branch is used for running evaluations with the deterministic benchmark EAs.
- PythonCommandLine branch is used for the grid search trivial tuning and data analysis.
- meta_opt branch is used for the development of the meta ea (CMA-ES) in Python.
- Under the main folder, use the Makefile (command "make") to compile.
- Run with java -jar testrun.jar -submission=player19 -evaluation=BentCigarFunction(or KatsuuraEvaluation/SchaffersEvaluation) -seed=1