A new strategy using Differential Evolution (DE) for Adaptive Plan System of Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) called DE-PSO-APGA is proposed to solve a huge scale optimization problem, and to improve the convergence towards the optimal solution. This is an approach that combines the global search ability of GA and Adaptive plan (AP) for local search ability. The proposed strategy incorporates concepts from DE and PSO, updating particles not only by DE operators but also by mechanism of PSO for Adaptive System (AS). The DE-PSO-APGA is applied to several benchmark functions with multi-dimensions to evaluate its performance. We confirmed satisfactory performance through various benchmark tests.