S.C. Maree, T. Alderliesten, D. Thierens, P.A.N. Bosman
The Hill-Valley Evolutionary Algorithm (HillVallEA) is a real-valued evolutionary algorithm specifically aimed for multi-modal optimization. It has been described initially in
Real-Valued Evolutionary Multi-Modal Optimization driven by Hill-Valley Clustering In Proceedings of the Genetic and Evolutionary Computation Conference S.C. Maree, T. Alderliesten, D. Thierens, and P.A.N. Bosman. GECCO-2018, ACM Press, New York, New York, 2018.
and benchmarked in the following technical reports
Benchmarking the Hill-Valley Evolutionary Algorithm for the GECCO 2018 Competition on Niching S.C. Maree, T. Alderliesten, D. Thierens, P.A.N. Bosman arXiv preprint arXiv:1807.00188, 2018.
and
Benchmarking HillVallEA for the GECCO 2019 Competition on Multimodal Optimization S.C. Maree, T. Alderliesten, P.A.N. Bosman arXiv preprint arXiv:1907.10988, 2019 .
Start by making a clone of the repository,
git clone https://github.com/SCMaree/HillVallEA
Two example scripts have been provided to demonstrate the use of HillVallEA. Call make to build using your favorite compiler. This builds the two provided example scripts, example_simple and example_cec2013_benchmark.
The script example_simple uses HillVallEA to solve the Six Hump Camel Back problem and example_simple.cpp can function as a guideline in order to implement your own problem.
The script example_cec2013_benchmark runs HillVallEA on the problems of the CEC2013 niching benchmark
reproduces the obtained peak ratio and static f1 averaged over a number of runs as stated in the above mentioned technical report.
To clean up after compilation, call make clean.