The authors have been developing the guidance system of winged rocket using dynamically distributed genetic algorithm (DynDGA) for trajectory optimization. DynDGA is an advanced genetic algorithm (GA) which can enhance the variety of trajectories and maintain the trajectory search performance. However, DynDGA requires higher computing power. One of the simple solution for this problem is to reduce the number of individuals and generations, but it also degrades the solution search capability. For the implementation, authors need to make a tradeoff between these problems. Evolutionary algorithms (EAs) have proven successful in a vast number of static applications and the number of papers produced in this area is growing rapidly. However, they also seem to be particularly suitable for dynamic and stochastic optimization problems such as natural selection. The authors performed some simulations, and the results succeeded to reach the target point. However, at some initial conditions, the simulation could not reach near the target point. This paper describes the simulation results of DynDGA onboard guidance system for experimental winged rocket in dynamic environment.