Prevention of PM2.5 is attracting increasing attention all over the world as PM2.5 can cause and exacerbate respiratory diseases. Compared with conventional natural ventilation and mechanical ventilation, air purifiers with particular filters are more efficient in the control of indoor PM2.5. Currently, there are limited studies on the operations of portable indoor air purifiers. To improve the efficiency of an air purifier in control of PM2.5, an optimal operational strategy is needed. This paper proposes a framework for the optimization of operations of air purifiers for control of indoor PM2.5 based on building information modeling (BIM) and computational fluid dynamics (CFD). A case study is conducted to validate the proposed optimization framework and the results are discussed. It can be shown from the results that the best location of the air purifier can increase efficiency by up to 33% compared with other locations.