In today's manufacturing processes, production optimization is very important to increase the competitive edge, so production managers are hardly trying to increase their production output (without increasing resources) by using different manufacturing processes and different fields of industrial engineering. These methods are used in productivity and decrease the cost of goods sold, which managers favor in all companies. This paper investigated the optimization problem in a flow shop production line with the probable time and the other constraints such as limited equipment, manufacturing process limit, by using scheduling techniques and creating a learning system by simulating. We use a simulation-based optimization approach that combines simulation and exact methods to solve the Flow Shop Scheduling problem. simulation software used to reduce the constraints and exact model used for optimizing answers that can be efficient and effective. Implementing this model with all its probable components in a high-tech pharmaceutical company with many different products increases utilization and largely to those outputs have increased by 12%. Manuscript profile