Determining the best process plan and route for each part is one of the main problems in dynamic stochastic systems. Therefore, multiple process plans are considered for each operation of each part (machine flexibility and/or part routing) and alternative operations (operation flexibility) simultaneously. In this paper, Optimization via Simulation (OvS) is utilized to plan the processes and route the parts in a dynamic stochastic flexible job-shop environment (DSFJS). Genetic algorithm (GA) which is envisaged to be the optimization component of OvS mechanism is integrated with the simulation model of the production system. A four-factor full factorial design is used to analyse the effect of main factors' and factor interactions' effects on the total of average flowtimes of each part performance of the shop. The design includes the flexibility level of the shop, number of parts, number of operations, and number of alternative process plans. Finally, the main findings of cases are summarized in the study.