Abstract: The isomerization of glucose to fructose is an important industrial process in obtaining high fructose syrup, a sweetener widely used in food industry. In this work, a hybrid simulated moving bed reactor (SMBR) system is optimized using experimentally verified dynamic SMB model to maximize the net productivity of HFS55 using minimum solvent. An adaptation of the state-of-the-art AI-based robust optimization technique, non-dominated sorting genetic algorithm with jumping genes (NSGA-II-JG) is used in finding the Pareto (non-dominated) solutions for both the existing as well as SMBR system at the design stage. Finally, SMBR configuration was modified to further improve the system performance. Systematic multi-objective optimization resulted in significant performance improvement. Moreover, the new optimization technique gives much faster, smoother and larger spread of the Pareto-optimal solutions. © 2004 Elsevier B.V. All rights reserved.