【摘要】 在化工过程合成中,人们在确定研究系统的最大超结构后,通常采用混合整数非线性规划模型将其表达,而后通过计算机对该模型求解,从而找到最佳的流程结构。然而,近年来出现了1种新的求解过程,称为加速分支定界法(ABB),是在最大结构已知的基础上,采用分支定界法进行求解的思路。该算法克服了传统方法在处理整型变量时出现的麻烦,不需要建立复杂的混合整数非线性规划模型,就可以实现计算机自动寻找最优的过程流程,为快速有效地求解化工过程综合优化问题提供了1种新的途径。本文对分支定界法与加速分支定界法进行了详细比较,证实了ABB算法在实现自动寻找最优流程结构的合理性与可靠性。最后,以生化法制备丁醇、乙醇和丙酮的下游分离提纯为实例,研究了ABB算法在过程优化中的应用。结果表明,该算法克服了传统方法在处理整型变量时出现的麻烦,是1种快速有效地求解化工过程综合优化问题的新途径。更多还原

【Abstract】 During process synthesis of chemical engineering,as the maximal structure was determined,the mixed-integer nonlinear programming (MINP) was always used to express it,and then the optimal flowsheet could be gained through computer-solving.Recently,one new solving approach called the Accelerated Branch and Bound(ABB) occurred,in which the Branch and Bound method(BB) was adopted to solved the synthesis problem as the maximal structure was known.ABB overcomes the troubles from traditional methods as the integer variable was addressed,and the optimal flowage-structure can also be grained automatically by computer without the establishment of intricate MINP model.BB and ABB were compared carefully in the paper,and the rationality and reliability of ABB was approved during the automatic search of the optimal structure.Finally,using the purification and separation process of bio-products(Butanol,Ethanol and Acetone) as an example,the application of ABB in process synthesis was studied.The result demonstrated that ABB was a rapid and effective approach to solve the process synthesis problem of chemical engineering.更多还原