Towards process, environment and economic based criteria for multi-objective optimization of industrial acid gas removal process

Acid gas removal is an important process to meet environmental regulations and protect machinery and pipelines. Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to optimize the process considering economic and environmental objectives. The optimization was carried out using excel-based multi-objective optimization (EMOO). Acid gas removal process using dimethyl ethers of polyethylene glycol is optimized considering profit, global warming potential and Human Toxicity. At the same time, the amount of sulfide removed from the gas and that of methane gas recovered also need to be maximized. The trade-offs are investigated by reviewing the effects of the process variables on the objectives. Two-objective cases are considered and the Pareto optimal solutions are obtained. A comparison and a three-objective case was carried out. Two-objective optimization gave better results in all the cases but the three-objective solutions would be more practical, given that industries generally operate around more than two objectives.