Multiobjective optimization of cyclone separators using genetic algorithm

Multiobjective optimization of a set of N identical reverse-flow cyclone se parators in parallel was carried out by using the nondominated sorting gene tic algorithm (NSGA). Two objective functions were used: the maximization o f the overall collection efficiency and the minimization of the pressure dr op. Nondominated Pareto optimal solutions were obtained for an industrial p roblem in which 165 m(3)/s of air was treated. In addition, optimal values of several decision variables, such as the number of cyclones and eight geo metrical parameters of the cyclone, are obtained. The study shows that the diameters of the cyclone body and the vortex finder, and the number of cycl ones used in parallel, are the important decision variables influencing the optimal solutions. This study illustrates the applicability of NSGA in sol ving multiobjective optimization problems involving gas-solid separations.