M Bayat - Department of Chemical Engineering, Faculty of Engineering, University of Bojnord, Bojnord,Iran

In this study, non-dominated sorting genetic algorithm-II (NSGA-II) is used for multiobjectiveoptimization of the fluidized bed methanol synthesis reactor. Inlet temperatureof gas phase (Tg), temperature of saturated water (Tshell), total molar flow rate (Ft)and inlet pressure of gas phase (Pt) are selected as decision variables. Methanolproduction rate and selectivity is maximized as two objective functions. The Shannon’sEntropy, LINMAP and TOPSIS methods as three decision making approaches areused to select the final solution of Pareto front. The optimization results enhancedabout ۵۵.۴% and ۴۸% methanol production rate and selectivity based on LINMAPmethods compared with the non-optimized fluidized bed methanol configuration. Theresults suggest that utilizing of the optimized-FBMR for enhancement of methanolproduction could be feasible and beneficial.

Multiobjective optimization; fluidized bed reactor; Methanol synthesis; NSGA-II;Decision making method