This paper presents an Adaptive Genetic Algorithm (AGA) where selection pressure, crossover and mutation probabilities are adapted according to population diversity statistics. Th...
In this paper we test whether a correlation exists between the optimal mutation rate and problem difficulty. We find that the range of optimal mutation rates is inversely proporti...
Recent results show that the Differential Evolution algorithm has significant difficulty on functions that are not linearly separable. On such functions, the algorithm must rely...
Andrew M. Sutton, Monte Lunacek, L. Darrell Whitle...
Abstract-- In evolutionary algorithms, the fitness of a population increases with time by mutating and recombining individuals and by a biased selection of more fit individuals. Th...
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...