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光气吸收塔是TDI生产中的一个重要设备,其操作要求塔顶气相出料中的光气含量、塔底液相出料中的HCl含量都尽可能低。选择合适的操作参数和设备参数,使两目标得以兼顾,而归结为一个多目标混合整数非线性规划(MOMINLP)的求解。本文在模块环境(Aspen Plus)下,建立了基于多目标遗传算法NSGA-Ⅱ求解MOMINLP的系统结构。编码为混合编码方式,整型变量采用二进制编码,实数变量采用实型编码。设计了遗传算法与Aspen Plus之间的接口程序,此接口不但传递数据,还具有二进制编码数据、模拟系统错误信息的处理功能。计算结果表明,遗传算法能够较好地给出Perato最优解集,本文提出的系统结构合理,可应用于一般化工流程的多目标优化综合。
Phosgene absorber is an important equipment in TDI production. Its operation requires the phosgene content in the overhead gas phase outgas and the HCl content in the liquid phase out of the bottom of the tower as low as possible. Select the appropriate operating parameters and equipment parameters, so that the two objectives can be taken into account, and boiled down to a multi-objective mixed integer nonlinear programming (MOMINLP) solution. In this paper, the system structure of MOMINLP based on multi-objective genetic algorithm NSGA-II is established under the Aspen Plus environment. Encoding for hybrid encoding, integer variables using binary encoding, real variables using real encoding. The interface program between genetic algorithm and Aspen Plus is designed. This interface not only transmits data, but also has binary coded data to simulate the processing function of system error message. The results show that genetic algorithm can give Perato optimal solution well, and the proposed system is reasonable and can be applied to multi-objective optimization synthesis of general chemical processes.