Multi-objective optimization of industrial natural gas sweetening process using elitist non-dominated sorting genetic algorithm is carried out for methyl di-ethanol amine absorbent to tune the process param-eters to improve absorption as well as regeneration performance. This study includes several operating parameters such as lean amine temperature and pressure, feed gas temperature and pressure, regenera-tor feed temperature and pressure, feed flow rate, etc. Environmental and economic optimization criteria are considered using four cases comprising of several conflicting objectives like net profit, global warm-ing potential, and acidification potential under two-objective and three-objective optimization scenarios. Constraints are imposed on H2S content and CO2 content as per the maximum permissible limit. Pareto optimal fronts are found for different cases and trade-offs between different objectives are illustrated. Simultaneous effects of different variables together on the conflicting objectives are considered to analyze the sweetening process to get a more economical and environmentally friendly process. (C) 2020 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.