The crude distillation unit (CDU) plays a significant role in the petroleum refinery. Decision variables of this unit have an effect on the final product quality, quantity, and energy consumption. The aim of this work is to increase the profit of the refinery proportionally with reducing emissions by getting high distillate products through selection of the optimal conditions. Two goal functions in three cases, namely, profit, CO2 emission, energy cost, and total distillate are considered. Therefore, the multi‐objective particle swarm optimization (MOPSO) algorithm is implemented by using MATLAB to optimize the CDU unit and then linked to an ASPEN HYSYS simulator. The effect of the temperature of preheated crude is demonstrated in the Pareto front. Also, the influence of the other variables, i.e., reflux ratio, atmospheric stripper steam, and amount of fuel burnt, is investigated.