PX Oxidation Process Optimization Based on Kriging Surrogate Model

Based on the process simulation model, complex chemical process optimization often takes a long time and has low efficiency. By using latin hypercube sampling and Kriging modeling method, a multiobjective optimization strategy based on Kriging model is proposed, then this strategy is applied to PX oxidation reaction process optimization. The simulation results show that the precision of the established Kriging surrogate model for three goals output is less than 1%. Improved multiobjective particle algorithm is used to optimize Kriging surrogate model, not only global optimal solution can be obtained, but also running time is saved obviously compared with the process simulation model. Therefore, Kriging model can take place of the PX process simulation model to realize optimization at the condition of meeting the requirement of accuracy, and has high optimization efficiency.