基于改进NSGA-Ⅱ算法的乙烯裂解炉操作优化

现有的乙烯裂解炉优化通常只针对两个目标函数即产物乙烯和丙烯的收率，并且采用遗传算法的收敛效果一般，故提出一种基于改进NSGA-Ⅱ算法来研究一个多目标运行的解决方案，以此来解决乙烯裂解炉的固定周期操作优化问题，即在增大产物乙烯和丙烯收率的同时减少原料以及蒸汽流量来提高整体运行状况。把具体问题量化为数学模型，分析了原料气烃比、原料流量、出口温度对乙烯和丙烯收率的影响。实验结果表明，相较于原有操作条件，提出的优化方案具有良好的可行性。

Operation optimization of ethylene cracking furnace based on improved NSGA-Ⅱ algorithm

The existing ethylene cracking furnace optimization usually only considers the two objective functions, namely the yield of ethylene and propylene; the convergence effect of genetic algorithm is not good enough. Therefore, an improved NSGA-Ⅱ algorithm is proposed to study a multi-objective operating solution for the fixed cycle operation optimization problem of the ethylene cracking furnace, which is to increase the ethylene and propylene yield while reducing the raw material and steam flow to improve the overall operation. We quantified the specific problem into a mathematical model and analyzed the effects of feed gas-to-hydrocarbon ratio, feedstock flow rate, and outlet temperature on the yield of ethylene and propylene. The experimental results show that compared with the original operating conditions, the proposed optimization scheme has good feasibility.