Ride Hailing service and Dynamic Shuttle is one of key smart mobility practices, which provide on-demand door-to-door ride-sharing service to customers through smart phone apps. On the other hand, some big companies spend millions of dollars yearly in third party vendors to offer employee shuttle services to pick up and drop off employees from designated locations and provide daily commutes for employees to and from work. Efficient routing algorithms and analytics are the key ingredients for operation efficiency behind these commercial services. They can significantly reduce operation costs by shortening bus routes and reducing bus number, while maintaining given the same quality of service. The study will develop an off-line optimization routing methods for employee shuttle services in some regions. First, based on the historical demand data collected from a factory in Thailand, we develop a constraint programming model to compute the optimal routes and number of shuttles needed. Many business and operation constraints are considered, such as number of shuttles, seat capacity, the road condition for shuttle types, maximum riding time and time window of the employee shift. The model is tested using historical operation data. It may propose optimal fixed routes for day shift due to large demands. As to other specific shifts, optimal flexible routes could be developed based on the changes of the demands. Finally, simulation model is developed a) to evaluate the performance of the algorithm, b) to understand the effectiveness and of the algorithm under different scenarios, and c) to study the robustness of the algorithm under uncertain demand.