How to cite
Xue, F., and Shen, G. Q. (2017). Design of an efficient hyper-heuristic algorithm CMA-VNS for combinatorial black-box optimization problems. In Proceedings of GECCO’17 Companion, Berlin, Germany, July 15-19, 2017, 6 pages. DOI: http://dx.doi.org/10.1145/3067695.3082054
How does it work
As its name, CMA-ES runs first, VNS then takes the baton from CMA-ES in the relay race. The semi-adapted covariance matrix model of CMA-ES can recommend promising candidates in VNS phase.
For more details, please refer to the papers.
When to use CMA-VNS
When your optimization problem is huge, expensive, way too complex.
Goal of this project
- To develop a competitive entry in CBBOC competitions
- To design an efficient way of solving complex NK-models
- To try to build a bridge between a derivative-free optimization method (CMA-ES) and a local search heuristic (VNS)
Copy files to src/ folder of CBBOC API
gcc src/*.cpp -Iinclude -Ipath_to_libcmaes -Ipath_to_Eigen -std=c++0x -lstdc++ -O3
How to contribute