一种新的DNA遗传算法及其在参数估计中的应用

A new DNA genetic algorithm and its application in parameter estimation

化工过程的参数估计是十分棘手的问题,为此常将这类问题转化为非线性优化问题来解决。遗传算法是一种适应性强的全局搜索方法,常被用于解决非线性系统的参数估计问题。但其局部搜索能力较差,易早熟。针对遗传算法的缺点,提出了一种新的DNA遗传算法。该方法使用碱基对个体进行四进制编码,受DNA分子操作启发设计了新的交叉和变异算子。两个经典测试函数的计算结果表明,该算法的搜索能力相对于其他两种算法有了明显提高。使用该算法来估计重油热解三集总模型中的参数,结果表明所建模型拟合精度高。

Parameter estimation of chemical processes can be presented as a tough optimization problem which can be solved with optimization methods.As a robust global searching method,genetic algorithm （GA） has been frequently applied in this area.However,the genetic algorithm has some shortcomings,such as weak local search ability and tends to premature.Furthermore,the encoding of GA cannot reflect the genetic information of biological organism.To overcome the deficiencies of GA,a new DNA genetic algorithm is proposed for the parameter estimation of chemical engineering processes.The proposed method uses nucleotide bases to present the individual. The novel crossover and mutation operators inspired by DNA molecular are designed.The novel crossover operators include permutation crossover operator and translocation crossover operator,and the novel mutation consists of anticodon mutation and maximum-minimum mutation.The solutions with two typical test functions show that the proposed method outperforms the other two methods in the searching speed,searching precision and the success rate.Finally,this method is applied to estimate the parameters of heavy oil thermal cracking model.The results of eight cross validation shows that the proposed algorithm possesses small self-check relative error,prediction relative error,and the standard deviation of relative error.Compared with the other two models,the model established by the proposed DNA genetic algorithm has smaller modeling error.