In recent years, simultaneous optimization of two conflicted objective functions become an important topic in power system. In this paper, a multi-objective mixed-integer linear programming (MILP) based model is provided for economic-environmental scheduling of a Smart apartment building. The first objective function is the operation cost of the building’ s minimization. The minimization of the CO2 emission is considered as the second objective function. The proposed multi-objective problem is solved using the weighted sum approach and the ɛ constraint method. Then, min-max fuzzy satisfying approach is carried out to select the ideal win-win strategy from the obtained efficient results. The proposed MILP-based sample model is solved using General Algebraic Modeling System (GAMS) under CPLEX solver. Also, two scenarios, weighted sum approach and ɛ-constraint method scenarios, are used to analyse the efficiency of the proposed sample model. By comparing the obtained results, it can be concluded that with considering the ɛ-constraint approach, total operation cost of the building is reduced 24. 78% by optimizing the model from economical perspectives. On the other hand, solving the proposed model from environmental perspectives led to a decline of 6. 96% in CO2 emission. Also, the weighted sum approach shows a reduction of 25. 11% and 10. 73% as a result from economic and environmental points of view, respectively.