摘要

A modification is proposed for the differential evolution algorithm which aims to improve its convergence performance. The modification embeds an additional operation, directed mutation, into an original version of the differential evolution. The aim of this operation is to increase the convergence velocity of the differential evolution and thereby to obtain an acceptable solution with a lower number of objective function evaluations. Such an improvement can be useful in many real-world problems where the evaluation of a candidate solution is a computationally expensive operation and consequently finding the global optimum or a good sub-optimal solution with the algorithm is too time-consuming, or even impossible within the time available. The modified version of the differential evolution was empirically examined with a suite of six well-known test problems and compared with the original version of the differential evolution algorithm. The obtained numerical simulation results suggested drawing a preliminary conclusion that the modified version statistically outperforms the original one.
Significance: The approach described can greatly improve efficiency, convergence velocity in particular, differential evolution by embedding a simple directed mutation operation into the original version of differential evolution. Numerical simulation of the method in solving a suite of function minimization problems shows good results.