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 ɛconstraint
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.