Abstract: Aromatic extraction is an important process of industrial aromatic production, its operation will affect greatly the overall efficiency of the aromatic complex. Product purity model and process energy consumption model are obtained based on simulation and response surface method, which are applied on the optimization of the process. A multi-objective optimization model is developed to maximize the product purity and minimize the energy consumption. An improved adaptive weighted sum method is proposed and used to solve the model. The results show that the new method can improve the efficiency without decreasing the uniformity of distribution of Pareto optimal solutions. The optimal operation parameters are given for different purity grades. The comparison between the results of optimization and the base case result shows that the optimal operation condition can increase product purity while decrease the energy consumption. The model and method proposed can effectively improve the accuracy of decision making in the operation optimization of aromatic extraction process.

Key words: aromatic extraction, multi-objective optimization, adaptive weighted sum method

摘要： 芳烃抽提是芳烃生产过程的重要环节，其生产调优对提高整个芳烃联合装置的效益具有重要意义。基于流程模拟及响应面分析方法，得到了芳烃抽提过程的产品纯度模型及能耗模型。建立了以产品纯度最大化及过程能耗最小化的多目标优化模型。提出了一种改进的自适应加权求和算法，并用于多目标优化模型的求解。求解结果表明新算法在Pareto最优解分布的均匀性上与原算法相当，但求解效率要高于原算法。给出了不同产品等级下的最佳操作参数，采用优化后的操作参数可有效地提高产品纯度并降低过程能耗。提出的多目标优化模型及求解算法用于芳烃抽提过程的操作调优，可有效地提高决策的准确性。

关键词: 芳烃抽提, 多目标优化, 自适应加权求和算法