In this study, a modified version of differential evolution (DE) is used to solve dynamic optimization problems
(DOPs). To promote the efficiency of the basic DE, the local replacement (LR) strategy is introduced to
intensify the search in the neighborhood of the current best solution. To solve by the proposed method, the DOP
is converted a nonlinear programming (NLP) problem via control vector parametrization (CVP). The final results
from two cases of DOP show that such modification is simple and effective in the promotion of convergent rate
and numerical accuracy.
