Multiobjective optimization of reactive distillation with thermal coupling using non-dominated sorting genetic algorithm-II

In this study, the Multiobjective optimization of transesterification reactive distillation column with thermal coupling by using Non-Sorting Genetic Algorithm II (NSGA-II) is presented. A Visual C++ (VC++) code for real-parameter NSGA-II and HYSYS software for thermodynamic calculation of reactive distillation (RD) column have been linked to optimize the effective parameters of reactive distillation column. The 9 parameters, Feed ratio, Reflux ratio, Methyl acetate temperature, n-Butanol temperature, Tray number of n-butanol feed, Tray number of methyl acetate feed, tray number of side stream, Molar flow of side stream, and pressure of reactive distillation column, are selected as decision variables. The specification value for simulation of reactive and non-reactive columns is 0.995 for purity of n-butyl acetate and methanol respectively. The Non-Sorting Genetic Algorithm II was employed for minimization of reboiler energy cost, maximization of n-butyl acetate molar flow as reactive distillation productivity, and maximization of methanol molar flow as non-reactive distillation column productivity. The NSGA-II proposed multiple solutions set as optimal solutions, but from these results, three set give better results than the others.

Schematic of transesterification reactive distillation with thermal coupling.Figure optionsDownload high-quality image (68 K)Download as PowerPoint slideHighlights
► The Multiobjective optimization of RD column with thermal coupling by using NSGA-II is presented.
► The nine parameters were selected as decision variable in optimization problem.
► The three important parameters have been selected as objective functions.
► Two scenarios with different maximum generation number have been selected for solving optimization problem.