Kinetic modeling and multi-objective optimization of an industrial hydrocracking process with an improved SPEA2-PE algorithm

Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases, naphtha, diesel, and other products through cracking reactions. Multi-objective optimization algorithms can help refining enterprises determine the optimal operating parameters to maximize product quality while ensuring product yield, or to increase product yield while reducing energy consumption. This paper presents a multi-objective optimization scheme for hydrocracking based on an improved SPEA2-PE algorithm, which combines path evolution operator and adaptive step strategy to accelerate the convergence speed and improve the computational accuracy of the algorithm. The reactor model used in this article is simulated based on a twenty-five lumped kinetic model. Through model and test function verification, the proposed optimization scheme exhibits significant advantages in the multi-objective optimization process of hydrocracking.