Vehicle scheduling is an important component of the transit operations planning process because it is directly related to the number of vehicles required for covering all trips. However, in practice, vehicles are not scheduled by a very efficient approach, related to the fact that all vehicles use one type of operation strategy—full operation strategy—for meeting unbalanced demand patterns. This paper proposes a methodology to reduce the required number of vehicles by adjusting a few trips to operate by other strategies, including limited stop, short turn, deadheading, and mixed strategies. This proposed methodology is based on a graphical human–machine interactive technique, called deficit function (DF). The DF allows schedulers to select a variable trip schedule for reducing the number of vehicles using optimal determination of the best applied strategies. The process of adjusting variable trips to accommodate different strategies may result in passenger travel time changes. Two optimization models are developed to minimize these changes and determine a set of stops served by the variable trip schedule. This proposed methodology has been applied to a detailed example and a case study in Paris, France. The results show that the adjustment of a few trips to use certain strategies can reduce the number of buses required by three.