Parameter Optimization of Hydrocracker using Multi-block Kriging Metamodeling within Discontinuous Operating Space

Optimization of operational parameters is essential for the industrial process, but it is expensive to optimize them with their rigorous mechanism models. Therefore, a series of novel surrogate-based optimization algorithms are popular recently. The main idea of surrogate-based optimization is that the complex mechanism model is replaced by a simple imitator when searching for the optimal solution within a certain region. Usually, this region is created by Latin hypercube sampling and considered as a continuous decision space. However, in practical engineering optimization, the whole operating space is not always continuous, resulting from various type of equilibrium constraints, e.g., material balance and energy balance. To bridge the gap between the requirement of continuity for surrogate- based optimization and the reality of discontinuity on feasible operating space, a multi-block Kriging surrogates-based intelligent optimization algorithm was proposed in this paper. With some prior knowledge on economical operation, the whole discontinuous operating space is divided into several promising continuous subregions. In the simulation study, a set of Kriging metamodels were utilized to represent the rigorous hydrocracker model at different subregions considering the catalyst life. Simulation results indicate the effectiveness of our proposed method, in which the inlet temperatures of all reaction beds were optimized under a given production condition.