This paper describes a new proposed strategy of Adaptive Plan System using Differential Evolution (DE) with Genetic Algorithm (GA) called APGA/DE to solve large scale optimization problems, to reduce a large amount of calculation cost, and to improve stability in convergence to an 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 new concept of AP using DE for Adaptive System (AS) with GA. The APGA/DE is applied to several benchmark functions with multi-dimensions to evaluate its performance. It is shown to be statistically significantly superior to other Evolutionary Algorithms (EAs), and Memetic Algorithms (MAs). We confirmed satisfactory performance through various benchmark tests.