Multi-Objective Optimization and Multi-Criteria Decision-Making Approach to Design a Multi-Tubular Packed-Bed Membrane Reactor in Oxidative Dehydrogenation of Ethane

Ethylene is a crucial chemical in the manufacturing of numerous consumer products. In recent years, the oxidative dehydrogenation of ethane (ODHE) technique has garnered significant interest as a means for ethylene production due to its high ethylene selectivity and energy efficiency, the availability of ethane as a feedstock, and catalysts that can improve the performance of the process. This work delves into determining the optimal operating conditions for the ODHE process within a multitubular packed-bed membrane reactor by formulating and resolving multiobjective optimization (MOO) problems. The elitist nondominated sorting genetic algorithm II (NSGA-II) method is employed in conjunction with three different multicriteria decision-making (MCDM) methods: (i) technique for order of preference by similarity to ideal solution (TOPSIS), (ii) preference ranking on the basis of ideal-average distance (PROBID), and (iii) simple additive weighting (SAW), to solve the MOO problems, obtain the optimal Pareto frontier, and recommend one solution for ultimate implementation. Through this approach, this work elucidates the trade-offs between ethane conversion, selectivity, and carbon dioxide production objectives, deepens the comprehension of their interrelationships, and underscores the effects of decision variables on the optimization objectives. The Pareto optimal set for optimizing C2H4 and CO2 annual production has the range of 4.78–80.14 kton and 0.195–13.24 kton, respectively. Consequently, this work provides practitioners with the insights needed for informed decision-making in ODHE process operation.