Managing event schedules on large scale introduces several challenges for decision makers, particularly with the existence of multiple limitations and considerations such as available resources, venues, audience, among others. To solve such complicated problem, we develop a multi-objective mixed-integer programming optimization model for resource-constrained event scheduling over a multiday planning horizon. The model aims to find the optimal location assignment for all events, and determine the starting day for each event within the overall season. Moreover, the model considers class-based structure, venues utilization, and seasonal continuity. Furthermore, we adopt a lexicographic multi-objective method, where the primary objective is to maximize the overall profit, while the secondary objective is to balance the utilization of venues. The efficiency of the model is illustrated through a dataset of 24 different events with five different types of audience to be scheduled across a 20-day season. Finally, conclusion remarks along with some potential future extensions are presented.