基于CSTR的反应器网络综合双层优化算法

反应器网络综合问题一般都是复杂的非线性规划问题，在分析基于全混流反应器的反应器网络模型特点的基础上，提出了求解该模型的双层优化算法. 通过将反应器网络综合非线性规划问题分解为物流流量和反应器体积空间的线性优化和浓度空间的优化搜索问题，降低了所求解问题的规模和难度，同时利用全局优化算法进行浓度空间的优化搜索，提高了求得全局最优解的概率. 实例研究表明，双层优化算法可以更准确地给出最优的反应器网络结构以及网络中反应器的类型和大小.

Two-level Optimization Algorithm for Reactor Network Synthesis Based on CSTR

The reactor network synthesis problems are commonly complex non-linear programming(NLP)problems,which are difficult to gain global optimal solutions using the traditional optimization approaches.To avoid the above disadvantage,a two-level optimization algorithm was proposed according to the characters of the reactor network model based on continuous stirred-tank reactors(CSTR).By this algorithm,the NLP of the reactor network synthesis is divided into the linear programming in flow rate and reactor volume space,and the stochastic optimization problem in concentration space.As a result the algorithm reduces the scales and difficulties of the problem.Meanwhile,by applying the global optimization algorithm to the concentration space optimization,the probability of obtaining the global optimal solution is improved.The results of the example studies show that the two-level optimization algorithm proposed can give better structure of the reactor network as well as the reactor type and size in the network.