Optimization of multicomponent isotopes separation cascades parameters using improved grey wolf optimizer algorithm

Abstract

The number of variables and design parameters in the multicomponent isotope separation cascades is considerable, and it is highly challenging to choose the best arrangement by obtaining the minimum interstage flow rate. Therefore, it is very important to develop a computational tool with high capability for calculating the cascade optimal parameters. The Improved Grey Wolf Algorithm, IGWO, is used in this study to develop an efficient code called the Isotopic Separation Real Code (ISRC-IGWO), which calculates the optimum parameters in the cascade for the separation of multicomponent mixtures. Investigations have been conducted in 4 separate tests to demonstrate this code's capability for computing the parameters with values close to the optimal conditions (in convergence to the near-optimal cascade). These evaluations have been carried out for both square and taper cascades, and different objective functions have been included in all tests. The findings show that ISRC-IGWO results are in agreement with optimal parameters calculation using other existing methods and IGWO is able to calculate cascade optimal parameters.