Building Optimization Model for Minimizing Operation and Maintenance Costs

Abstract

Building operation and maintenance costs are reported to be the longest and most costly phase of a building’s lifecycle and it exceeds the total cost of initial design and construction. The present study focuses on developing a new model for optimizing the upgrade and maintenance interventions for existing commercial and residential buildings to minimize their operation and maintenance costs in a predefined period of study while complying with specified annual budgets and building operational performance constraints. The optimization model is developed in three stages: (1) identifying model decision variables, formulating objective function, and constraints; (2) implementing model computations using binary linear programming; and (3) analyzing the performance of the optimization model using a case study. To ensure that the model generates practical solutions, it integrated a set of constraints to comply with annual budgets, components’ service lives, and expected operational performance. The results of the case study analysis showed that the developed model was able to identify the minimum building operation and maintenance costs associated with various annual operational budgets that ranged from $165K to $300K and for a study period of 20 years. The model is designed to generate an action report of maintenance and upgrade interventions that include detailed recommendations on the building components and equipment repair, replacement, and upgrade for each year in the study period.