Abstract I ndoor E nvironment Q uality (IEQ) of an office has significant effects on the performance and productivity of its occupants. There are several factors that have positive or negative impacts on occupants’ overall satisfaction, including the level of thermal comfort, visual comfort, aural comfort and I ndoor A ir Q uality (IAQ). While keeping energy savings objectives, energy management system can provide acceptable thermal comfort, visual comfort, and IAQ levels, by taking energy-related decisions. Several inputs that are changing continuously, such as energy prices, sets of indoor and outdoor environment parameters, occupants’ presence, activities and preferences are required for timely energy-related decision-making. Therefore, there is a need for a well-structured method to reach optimum decisions for energy costs and occupants’ IEQ. The main interest of this research is to propose a M ulti- O bjective Op timization (MOOP) method for energy and comfort management in commercial buildings. The proposed method is capable of providing situation-specific economic optimum indoor conditions, based on the combination of thermal comfort, IAQ, and energy costs, as well as energy prices, occupancy information and types of occupants’ activities. Operation of the proposed method is analyzed by annual energy performance simulation of a commercial building in Montreal, Canada. Based on provided results, the proposed MOOP method is capable of improving productivity of occupants, by up to $1000 per year per person, while reaching energy savings objectives. It is observed that potential for productivity improvement is higher during the swing and warm seasons, compared to the cold season. Having ability of flexible decision-making, the proposed MOOP method is suitable for I ntelligent E nergy M anagement S ystems (IEMSs), with objectives of maximizing energy costs and comfort conditions.