Cloud computing is an inevitable progression in the future computing development of technology. Its critical significancelies in its ability to provide all users with tremendous performance and reliable calculation.   With the evolution of system virtualization and Internet technologies, Cloud computing has emerged as a new computing platform. Cloud computing is to contribute virtualized IT resources as cloud services by using the Internet technology. In Cloud computing, a cloud user carry out an agreement called Service Level Agreement (SLA) with a cloud provider. The cloud user makes use of IT resources like storage and server as a service and pays for the service. In cloud computing environment, there are inevitably numerous service providers to provide services with similar functionalities and different QoS. These services can incorporate tens of thousands composite services with similar functions and different QoS. That is, there are many distinct combination plans. Therefore, in a service composition process, we need to choose service components from enormous services with similar functions and different QoS based on user's QoS requirements. In the research work, we used populations with different sizes, with adopted for different composition scales, the efficiency of algorithm has been greatly improved. Therefore, the research work concentrated on examining the dynamic adaptive approach of population size. The other next step is to apply the proposed hybrid algorithm into a number of functional large-scale services of computing environments, in order to enhance the efficient and reliable operations of the hybrid GA further. To analyzed the behavior of the proposed method using various research parameters such as Input number of tasks, Populations size( different), Average number of candidate services for each task, Compute average fitness value of simple genetic.