Multiobjective Optimization and Decision-making Method in Sorption-Enhanced Fluidized bed Reactor for DME Synthesis

In this study, a novel fluidized bed reactor for DME synthesis in the presence of in-situ water adsorbent namely Sorption Enhanced Fluidized-bed Reactor (SE-FMR) is optimized. The Non Dominated Sorting Genetic Algorithm-II (NSGA-II) is used for multi-objective optimization of this configuration. DME production rate and selectivity are maximized as two objective functions. The Shannon’s Entropy, LINMAP and TOPSIS methods as three decision making approaches are used to select the final solution of Pareto front. The optimization results enhanced about 362.32 and 173.32 ton/day DME production rate and CO2 utilization, respectively, based LINMAP methods compared with the conventional DME configuration.