MPS is a simple and effective continuous optimization metaheuristic algorithm, especially suited for solving multimodal optimization problems.
In the near future, this repository will contain C, MatLab and Python implementations. Some hybrid algorithms are on their way too.
- A. Bolufé-Röhler and S. Chen, "Minimum population search - Lessons from building a heuristic technique with two population members," 2013 IEEE Congress on Evolutionary Computation, Cancun, 2013, pp. 2061-2068. doi: 10.1109/CEC.2013.6557812, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6557812&isnumber=6557545
- A. Bolufé-Röhler and S. Chen, "Extending Minimum Population Search towards large scale global optimization," 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, 2014, pp. 845-852. doi: 10.1109/CEC.2014.6900374, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6900374&isnumber=6900223
- A. Bolufé-Röhler, S. Fiol-González and S. Chen, "A minimum population search hybrid for large scale global optimization," 2015 IEEE Congress on Evolutionary Computation (CEC), Sendai, 2015, pp. 1958-1965. doi: 10.1109/CEC.2015.7257125, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7257125&isnumber=7256859
- Bolufé-Röhler, Antonio and Coto-Santiesteban, Alex and Rosa-Soto, Marta and Chen, Stephen, Minimum Population Search, an Application to Molecular Docking (September 23, 2014). Gecontec: Revista Internacional de Gestión del Conocimiento y la Tecnología, Vol. 2 (3) 2014 . Available at SSRN: https://ssrn.com/abstract=2500219