A Self-Reconfiguring architecture supporting multiple objective functions in genetic algorithmsA Self-Reconfiguring architecture supporting multiple objective functions in genetic algorithms Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-11-152009enGenetic algorithms (GA) are search algorithms based on the mechanism of natural selection and genetics. FPGAs have been widely used to implement hardware-based genetic algorithms (HGA) and have provided speedups of up to three orders of magnitude as compared to their software counterparts. In this paper, we propose a parameterized partially reconfigurable HGA architecture (PPR-HGA). The novelty of this architecture is that it allows for the objective function to be updated through partial reconfiguration, and supports various genetic parameters.http://creativecommons.org/licenses/by/4.0/453-456International Conference on Field Programmable Logic and Applications, 2009 Papaefstathiou Ioannis Παπαευσταθιου Ιωαννης Effraimidis C. Papadimitriou Kyprianos Παπαδημητριου Κυπριανος Dollas Apostolos Δολλας Αποστολος Institute of Electrical and Electronics Engineers Γενετικοί αλγόριθμοι Genetic algorithms