基于改进NSGA-Ⅱ算法的氯乙烯精馏过程多目标优化

Multi-Objective Optimization Based on the Improved NSGA-Ⅱ Zlgorithm for Vinyl Chloride Rectification Process

(辽宁石油化工大学信息与控制工程学院,辽宁抚顺113001)

School of Information and Control Engineering, Liaoning Shihua University, Fushun Liaoning 113001, China

关键词: 氯乙烯精馏, 流程模拟, 多目标优化, 非支配排序遗传算法

A new improved non-dominated sorting genetic algorithm (NSGA-II) is studied aiming at solving the low purity, high energy consumption problems existed in vinyl chloride rectification process. The method can be used to solve the multi-objective optimization problem of vinyl chloride rectification process. The multi-objective optimization function with the energy consumption and purity of vinyl chlorides based on considering the various constraints of the mechanism model and the actual production conditions were established through the sensitivity analysis for the main operating parameters such as the feeding position and reflux ratio of high and low boiling tower and so on. Finally, the objective function is solved by using the improved NSGA-II. Compared to the NSGA-II, the experimental results show that the improved algorithm can get more uniform distribution of Pareto optimal solution set, which provides a strong support for the selection of parameters in the process of vinyl chloride distillation.

国家自然科学基金资助(61203021);辽宁省科技攻关项目(2011216011);辽宁省自然科学基金项目(2013020024);辽宁省高等学校杰出青年学者成长计划(LJQ2015061)。

10.3696/j.issn.1672-6952.2016.02.014