Natural gas is one of the most important sources of energy and power production in the world and normally it requires to be treated and conditioned. One of the treatment units is called gas sweetening unit which aimed to remove the acid gases associated with the natural gas. Multi-Objective optimization for two gas sweetening units from local Omani industry is conducted using non-dominated sorting genetic algorithm (NSGA-II) optimization technique. Unit-1 is using a blend of methyl di-ethanol amine and Piperazine solvent since carbon dioxide is the main acid gas contributor in the feed sour gas along with low concentration of hydrogen sulfide whereas Unit-2 use methyl di-ethanol amine only solvent in order to reduce the hydrogen sulfide and carbon dioxide to allowed possible restrictions. The problem formulated to have different design variables like feed gas pressure, feed gas temperature, feed molar flow, MDEA & Piperazine concentrations, regeneration pressure & temperature and lean amine temperature. Constrains forced on maximum allowable limit of carbon dioxide concentration and hydrogen sulfide concentration in sweet gas stream which are 2 mole% and 4 ppm respectively. The study is optimized from different perspective like process, economic, environmental, safety and thermodynamic point of views by developing different cases of two conflicted objective functions as well as for three objective functions. The objective function involve in this study are carbon dioxide removal, hydrogen sulfide removal, hydrocarbon recovery, return on investment (ROI), payback period (PBP), global worming potential (GWP), damage index (DI) and thermodynamic efficiency. The simultaneous effect of changing the design variables on the objective functions are plotted to analyze the sweetening units. These results obtained from this study are considered as the best design variables that will lead to improve the performance of the absorption and regenerations units for these two units.