(470f) Multi-Objective Optimization and Validation of a Simulating Moving Bed

Simulating moving bed (SMB) processes are widely used in sugar, petrochemical, and pharmaceutical industries. However, determining the design and operating parameters of SMB processes remains a challenging problem. The optimization problem is complicated by the relative large number of decision variables (such as flow rates, particle size, column length and configuration) and various conflicting objectives (such as maximization of the adsorbent productivity and the product purity and recovery). A multiple objective optimization technique is adopted. The solution of the optimization problem is given by an optimum Pareto set, which is a set of operating conditions such that no operating condition can be found that would lead to objective values with are all better that those in the Pareto set. The feasibility of the approach is demonstrated by on a hydrolyzed sugar beet pulp, separating a mixture of sugars and sugar acids. Experimental results on lab scale are presented and discussed.