Abstract: In the report, self-adaptive differential evolution algorithm based on the simplex search (SSADE) was proposed to solve the premature convergence and low precision of standard differential evolution (DE) applied for the optimization of high-dimensional complex function. The SSADE hybrid algorithm organically integrated DE algorithm which has powerful global search capability with the simplex search method which has strong local search ability, and which further improved the precision of solution. The parameter self-adaptive adjustment maintained the diversity of the population, the self-adaptive mutation strategy expanded the search range of the individual, enhanced the effect of the algorithm optimization. The simulation results confirmed the effectiveness of the new hybrid algorithm.