热偶精馏过程模拟优化方法的改进——人工神经网络-遗传算法

ADVANCEMENT OF SIMULATION AND OPTIMIZATION FOR THERMALLY COUPLED DISTILLATION USING NEURAL NETWORK AND GENETIC ALGORITHM

采用人工神经网络和遗传算法对热偶精馏分离过程提出了一种新的建模方法和优化算法 ,该方法不仅能够有效地求解热偶精馏过程的数学模型 ,迅速地得到优化变量和目标函数的解 ,而且具有获得全局最优解的能力 .

Thermally Coupled Distillation Columns are more efficient than conventional sequences. Because of the difficulties of proper design, their applications are restricted. A new approach using genetic algorithm and artificial neural network for the optimization of thermally coupled distillation is presented. Mathematical model constructed with artificial neural network based on the simulation results with ASPEN PLUS. The Comparison of ANN prediction results and ASPEN PLUS simulation results shows that the model can simulate thermally coupled distillation rightly. Modified genetic algorithm is used to optimize the artificial neural network model. With the proposed model and optimization algorithm, the decision variables and the target value can be solved automatically and quickly. The convergence curve proves the efficiency of the genetic algorithm. A practical example is used to demonstrate the algorithm.