engleski

Improving Convergence Properties of the Differential Evolution Algorithm

Differential evolution is a relatively novel evolutionary algorithm for solving general type of numeric optimization problems. Its simplicity and good convergence properties have been the reason for its broad application in practical scientific and engineering problems. Although convergence properties of differential evolution algorithm for modestly dimensioned problems reported in the literature were judged as excellent, analyses of algorithm's performance are still rather elementary. This work presents results of the study in dynamics of the algorithm on a set of constrained optimization problems. Results and insight gained in the numerical experiments suggested introduction of population refreshment mechanism into the basic differential evolution algorithm, in order to prevent stagnation but also to improve the convergence speed of the algorithm

evolutionary algorithm; differential evolution; convergence properties; population diversity; efficiency; improvements

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