Rail systems are preferred to find sustainable solutions to traffic problems in cities with high population density. To increase the use of public transport without reducing service quality, it is essential to construct a demand-based timetable. In this study, a mathematical model that meets the passenger demand in cases of over and under-saturation, considers structural-operational constraints, aims minimum energy consumption and machinist costs is presented. Passenger demands are forecasted using four popular techniques. In both over and under-saturated situations, it is possible to meet passenger demand by using adaptive headways and determining train specifications as coupled or decoupled. Moreover, a comfort coefficient is incorporated in the model to adjust the service quality of the trip. To demonstrate the performance of the proposed MILP model, Kayseri Ulasim A.S. timetabling problem is solved. The effect of different passenger demand levels, over and under-saturated cases, on headways and train types is analysed.