Bugajski, I., Listkiewicz, P., Byrski, A., Kisiel-Dorohinicki, M., Korczynski, W., Lenaerts, T., Samson, D., Indurkhya, B., & Nowé, A. (2016). Enhancing particle swarm optimization with socio-cognitive inspirations. In Procedia Computer Science (Vol. 80, pp. 804-813) https://doi.org/10.1016/j.procs.2016.05.370

@inproceedings{9d8237f98cfb41a794ce5a10b37dc61c,
title = "Enhancing particle swarm optimization with socio-cognitive inspirations",
abstract = "We incorporate socio-cognitively inspired metaheuristics, which we have used successfully in the ACO algorithms in our past research, into the classical particle swarm optimization algorithms. The swarm is divided into species and the particles get inspired not only by the global and local optima, but share their knowledge of the optima with neighboring agents belonging to other species. Our experimental research gathered for common benchmark functions tackled in 100 dimensions show that the metaheuristics are effective and perform better than the classic PSO. We experimented with various proportions of different species in the swarm population to find the best mix of population.",
keywords = "Metaheuristic computing, Nature-inspired computing, Swarm intelligence",
author = "Iwan Bugajski and Piotr Listkiewicz and Aleksander Byrski and Marek Kisiel-Dorohinicki and Wojciech Korczynski and Tom Lenaerts and Dana Samson and Bipin Indurkhya and Ann Now{\'e}",
year = "2016",
doi = "10.1016/j.procs.2016.05.370",
language = "English",
isbn = "1877-0509",
volume = "80",
pages = "804--813",
booktitle = "Procedia Computer Science",
note = "International Conference on Computational Science , ICCS ; Conference date: 06-06-2016 Through 08-06-2016",
url = "https://www.iccs-meeting.org/iccs2016/",
}