Usually, methanol is produced from synthesis gas using copper, zinc oxide catalyst with alumina oxide. It is considered as one of the main raw materials and a building block for many essential chemicals in the industry. A multi-objective optimization study is applied to the Lurgi two-step methanol synthesis process using the non-dominated genetic sorting algorithm NSGA-II. In order to achieve process, economic and environmental objective functions and find the Pareto fronts. Seven different cases are developed involving two or three conflicting objectives. The objective functions studied in this thesis are methanol production, yield, selectivity, profit, overall carbon conversion, total energy, and total annual CO2 emission. The problem formulated has five different decision variables, which are syngas molar flow, reactor feed pressure, reactor 1 temperature, reactor 2 temperature, and by-product mass flow in the methanol distillation column. The allowable limit of ethanol mole fraction in the produced methanol stream is less than 0.01 and methanol mole flow in the water to the treatment stream is less than 15 kmol/hr, these two limits are specified as the problem constraints. The optimized case results are compared with the base case to make sure that the set study objectives are achieved successfully. The effects of changing the decision variables simultaneously in the objective functions are plotted to analyze the methanol Lurgi process. Where the optimal operating conditions are found in order to maximize methanol production by 10.11%, maximize profit by 142.65%, minimize CO2 emission by 47.22%, and reduce total energy by 36.55%: syngas molar flow, reactor feed pressure, reactor 1 temperature, reactor 2 temperature, and by-product mass flow in the methanol distillation column must be respectively equal to 40021.19 kmol/hr, 80.1 bar, 233.58 °C, 202.80 °C, and 3.74 tonne/hr.