FPGA Implementation of a Multi-Population PBIL Algorithm

João Paulo Coelho, Tatiana M. Pinho, José Boaventura-Cunha

2015

Abstract

Evolutionary-based algorithms play an important role in finding solutions to many problems that are not solved by classical methods, and particularly so for those cases where solutions lie within extreme non-convex multidimensional spaces. The intrinsic parallel structure of evolutionary algorithms are amenable to the simultaneous testing of multiple solutions; this has proved essential to the circumvention of local optima, and such robustness comes with high computational overhead, though custom digital processor use may reduce this cost. This paper presents a new implementation of an old, and almost forgotten, evolutionary algorithm: the population-based incremental learning method. We show that the structure of this algorithm is well suited to implementation within programmable logic, as compared with contemporary genetic algorithms. Further, the inherent concurrency of our FPGA implementation facilitates the integration and testing of micro-populations.

Paper Citation

in Harvard Style

Coelho J., Pinho T. and Boaventura-Cunha J. (2015). FPGA Implementation of a Multi-Population PBIL Algorithm . In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA, ISBN 978-989-758-157-1, pages 279-286. DOI: 10.5220/0005610402790286

in Bibtex Style

@conference{ecta15,
author={João Paulo Coelho and Tatiana M. Pinho and José Boaventura-Cunha},
title={FPGA Implementation of a Multi-Population PBIL Algorithm},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,},
year={2015},
pages={279-286},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005610402790286},
isbn={978-989-758-157-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,
TI - FPGA Implementation of a Multi-Population PBIL Algorithm
SN - 978-989-758-157-1
AU - Coelho J.
AU - Pinho T.
AU - Boaventura-Cunha J.
PY - 2015
SP - 279
EP - 286
DO - 10.5220/0005610402790286