AbstractBuilding operation and maintenance costs are reported to be the longest and most costly phase of a building’s life cycle, where it exceeds costs of design and construction. Although buildings are regularly maintained, water- and energy-saving investments are not often analyzed. This paper presents the development of a novel model for optimizing the selection of upgrade and maintenance interventions for existing buildings to minimize their equivalent annual operation and maintenance cost (EAOMC) while complying with specified annual budgets and building operational performance. The optimization model is developed in three main phases that focus on (1) identifying model decision variables and formulating objective function and constraints; (2) implementing the model computations using binary linear programming; and (3) analyzing the performance of the optimization model using a case study. The primary contributions this research adds to the body of knowledge are (1) a new computationally efficient model for identifying optimal selection of building upgrade and maintenance interventions to minimize EAOMC; (2) modeling reactive, preventive, and predictive maintenance strategies based on component types; (3) integrating a simulation-based upgrade and maintenance approach to evaluate energy and water consumption of buildings; and (4) integrating maintenance and upgrade interventions to maximize economic benefits from building operation by reducing operational and maintenance costs. The results of the case study illustrated the new capabilities of the model in identifying optimal upgrade and maintenance interventions for various operational budgets with up to 32% reduction in EAOMC.