Το έργο με τίτλο High-speed FPGA-based implementations of a genetic algorithm από τον/τους δημιουργό/ούς Papaefstathiou Ioannis, Papadimitriou Kyprianos, Vavouras Michalis διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού 4.0 Διεθνές
Βιβλιογραφική Αναφορά
M. Vavouras, K. Papadimitriou, I. Papaefstathiou, "High-speed FPGA-based implementations of a Genetic Algorithm," in International Symposium on Systems, Architectures, Modeling, and Simulation, 2009, pp. 9 - 16. doi: 10.1109/ICSAMOS.2009.5289236
https://doi.org/10.1109/ICSAMOS.2009.5289236
One very promising approach for solving complex optimizing and search problems is the Genetic Algorithm (GA) one. Based on this scheme a population of abstract representations of candidate solutions to an optimization problem gradually evolves toward better solutions. The aim is the optimization of a given function, the so called fitness function, which is evaluated upon the initial population as well as upon the solutions after successive generations. In this paper, we present the design of a GA and its implementation on state-of-the-art FPGAs. Our approach optimizes significantly more fitness functions than any other proposed solution. Several experiments on a platform with a Virtex-II Pro FPGA have been conducted. Implementations on a number of different high-end FPGAs outperforms other reconfigurable systems with a speedup ranging from 1.2x to 96.5x.