Multi-criteria optimization of the process of electrolytic alkali’s evaporation in order to develop a resource-saving chemical-technological system

Abstract

Development of resource-saving chemical-technological systems requires maintenance of process parameters within the specified limits. The article describes the use of artificial neural networks for modeling of technological process of electrolytic alkali evaporation. The simulation was carried out in Statistica software. The simulation results were used to perform multi-criteria optimization by proper simplex minimization and Nelder-Mead minimization methods to reduce costs and improve process performance and product quality.