| The Differential Evolution (DE) algorithm goes back to the class of Evolutionary Algorithms and inherits its philosophy and concept. Possessing only three control parameters (size of population, differentiation and recombination constants) DE has promising characteristics of robustness and convergence. In this paper we introduce a new principle of Energetic Selection. It consists in both decreasing the population size and the computation efforts according to an energetic barrier function which depends on the number of generation. The value of this function acts as an energetic filter, through which can pass only individuals with lower fitness. Furthermore, this approach allows us to initialize a population of a sufficient (large) size. This method leads us to an improvement of algorithm convergence. |
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