Nowadays, the design of energy efficient and comfortable building results as the solution to a complex optimization that involves a great number of interdependent variables. In such a complex system that is characterized by many requirements, sometimes conflicting, the use of an integrated design approach can speed up the design process, allow evaluating and comparing a great number of design options and lead to optimized performance at multiple levels. We present the conception of a replicable methodology, including the integrated tools and metrics, for supporting the integrated design of the building envelope, aiming at minimizing the building total energy demand (resulting from the sum of heating, cooling and lighting energy needs) in a thermal and visual comfort context. The methodology relies on a simulation-based optimization process. For each of the two thousand of design solutions that are analyzed within the design space of the problem, the thermal and visual comfort conditions are evaluated at the same time. A "filter" approach is used for combining the different objectives. The methodology is applied to the design of a school classroom as a reference case study. Results are compared for four different building orientations and two different climatic conditions. The differences in design between the optimized building configurations in the different location and orientation emerge from the study, however resulting in similar energy performance (total primary energy demands in the range 78.6-82.8 kWh/m(2)y for Turin and 57.7-60.1 for Palermo). In all cases, energy-optimal solutions result as nearly optimal also from the comfort point of view, which demonstrate the validity of the implemented total energy approach. Beyond the numerical results, we provide an effective integrated methodology that is able to support designers in defining a unique energy and comfort optimized solution to be implemented in the real design analyzing the design space and determining the optimal set of passive solutions to minimize the total energy needs of a building in a context of good comfort conditions, going beyond the Pareto optimality concept and without dealing through complex multi-objective optimization processes. (C) 2018 Elsevier B.V. All rights reserved.