  Ethylene is a crucial chemical in manufacturing 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 multi-tubular packed-bed membrane reactor by formulating and
resolving multi-objective optimization (MOO) problems. The elitist
non-dominated sorting genetic algorithm II (NSGA-II) method is employed in
conjunction with three different multi-criteria 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 conflicting objectives, deepens the comprehension of their
interrelationships, and underscores the effects of decision variables on the
optimization objectives. Consequently, this work provides practitioners with
the insights needed for informed decision-making in the ODHE process operation.
