There is a strong relationship between occupants' comfort and their productivity. Indoor environmental conditions have impacts on the mental and physical well-being of occupants that subsequently, influence their productivity. Generally, occupants in a shared space have varied preferences for the thermal conditions of the indoor environment. For energy management systems of office buildings, inability to acknowledge occupants' thermal preferences may cause productivity losses. Salaries of office workers are many times higher than the costs of energy consumption, hence, improving the productivity of office workers can offer significant economic benefits. The main interest of this research is to propose a Multi Objective Optimization (MOOP) method for personalized energy and comfort management in offices. The MOOP method simultaneously optimizes the energy costs and collective productivity of office workers, by proposing Pareto optimal solutions for the automated control of the indoor environment, based on occupants' thermal preferences and Indoor Air Quality (IAQ). Alongside thermal preferences and IAQ, several continuously changing inputs are also considered including indoor and outdoor environmental parameters, energy exchange processes across the building zones, energy prices, occupants' presence, productivity rates, and thermal behavior. Application of the proposed method for personalized energy and comfort management is analyzed by the annual energy performance simulation of an office building, located in Montreal, Canada. Based on the provided results, the proposed method has the flexibility to manage the diversity among the thermal preferences of occupants, and significantly improves the productivity of office workers while optimizing the energy consumption costs. (C) 2017 Elsevier B.V. All rights reserved.