Multiobjective optimization of a continuous pulp digester

Abstract A rigorous dynamic model of the Kamyr continuous pulp digester has been developed as a distributed-parameter system. The model was adjusted based on data from an industrial unit. Optimal operating strategies are generated by a multiobjective optimization method based on Genetic Algorithms, aiming to control the kappa number and the pulp yield. Manipulated variables include the temperature of the liquor and chips fed in the digester and the inlet white liquor flow rate. The simulated results have confirmed the efficiency of the multiobjective technique to find the Pareto optimal set, offering a viable strategy to solve such complex dynamic optimization problems.