In this paper, we propose a technique to flexibly implement genetic algorithms for various problems on FPGAs. For the purpose, we propose a basic architecture for GA which consist...
In this study, a new mechanism that adapts the mutation rate for each locus on the chromosomes, based on feedback obtained from the current population is proposed. Through tests us...
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
Real-world multi-objective engineering design optimization problems often have parameters with uncontrollable variations. The aim of solving such problems is to obtain solutions t...
This paper presents a novel discrete population based stochastic optimization algorithm inspired from weed colonization. Its performance in a discrete benchmark, timecost trade-off...