This paper proposes a multi-objective optimization for the optimal energy scheduling of renewable-based energy system. The proposed model simultaneously considers both economic and environmental indices in the operation planning to present a comprehensive scheduling for the energy system. The studied energy system integrates the electrical, heating, and cooling sectors to increase the synergy, reliability, and flexibility of the renewable-based energy system. This integration improves the utilization of renewable energy system because the surplus generation of photovoltaic and wind energy can be converted to other forms of energy to supply the required heat and cooling energy of the system. In addition, Shannon entropy and multi-attribute utility theory (MAUT) are used to determine the relative importance of economic versus environmental criteria and to prioritize the solutions based on the operator’s viewpoint. The proposed model is tested on a standard case study and the numerical results present that the proposed model improves the emission of greenhouse gases by 4.8 % compared to single objective optimization in the normal condition. Also, compared to the scenario where no demand response is present, the demand response programs decreases the operating cost of the multi-energy system by 2.47 %.