生化系统稳态优化的多目标规划与双层规划方法研究

发布时间：2018-05-19 05:54

本文选题：生化系统 + 稳态优化　；参考：《渤海大学》2017年硕士论文

【摘要】：生物技术正处于迅速发展的时期,生化系统工程的地位也越来越重要了。但是由于生化过程具有非线性、时变性和不确定性等特点,所以学者们很难对它进行优化和控制。此外,在现实生活生产中,需要考虑的目标往往不仅仅是一个而是两个甚至更多。并且各目标之间往往是相互冲突、相互制约的。因此,怎样提高原材料的转化率和目的产物的产率进而提高整个生化行业的生产水平,是研究人员对生化系统研究的重中之重。本文研究了生化系统的稳态优化问题。论文研究的主要内容和取得的结果如下:1.针对生化系统的多目标稳态优化问题,在S-系统框架下提出了一种可求其最优解的新方法。首先把生化系统的常微分方程模型改写成S-系统形式,从而得到生化系统多目标稳态优化问题的S-系统形式;然后在对数空间下将得到的多目标非线性优化问题转化为多目标线性规划问题;再基于NBI(Normal Boundary Intersection)方法把多目标线性规划问题转化为一系列单目标线性优化问题来求解。与加权和及遗传算法相比,本文方法计算结果可以获得分布更加均匀的Pareto最优解。2.针对一类生化系统的稳态优化问题,本文在GMA(Generalized Mass Action)系统框架下,提出了一种双层规划优化模型,其外层优化问题的目标函数为通量的最大化;其内层优化问题的目标函数为生化系统代谢成本的最小化。为了有效求解所提出的双层规划模型,首先将外层和内层目标函数表示为幂函数形式,然后应用对数变换将双层规划问题转化为相对简单的新问题,最后应用线性规划的对偶理论将得到的新双层问题转化为单层非线性优化问题,并对其进行求解。计算研究表明,本文方法得到的计算结果比已有方法更具实际意义。
[Abstract]:Biotechnology is in a period of rapid development, and the status of biochemical systems engineering is becoming more and more important. However, because biochemical processes are nonlinear, time-varying and uncertain, it is difficult for scholars to optimize and control them. Moreover, in real life production, the goal to consider is often not just one but two or more. And the goals often conflict and restrict each other. Therefore, how to improve the conversion rate of raw materials and the yield of target products, and then improve the production level of the whole biochemical industry, is the most important research on biochemical system. In this paper, the steady-state optimization of biochemical systems is studied. The main contents and results of this paper are as follows: 1. A new method for solving the multiobjective steady-state optimization problem of biochemical systems is proposed under the framework of S- system. Firstly, the ordinary differential equation model of biochemical system is rewritten into the form of S- system, and the S- system form of multiobjective steady-state optimization problem of biochemical system is obtained. Then the multi-objective nonlinear optimization problem is transformed into a multi-objective linear programming problem in logarithmic space, and then the multi-objective linear programming problem is transformed into a series of single-objective linear optimization problems based on NBI(Normal Boundary intersection. Compared with weighted sum and genetic algorithm, the proposed method can obtain a more uniform Pareto optimal solution. 2. For a class of steady state optimization problems of biochemical systems, a bilevel programming optimization model is proposed under the framework of GMA(Generalized Mass action system. The objective function of the outer optimization problem is flux maximization. The objective function of the inner optimization problem is to minimize the metabolic cost of biochemical systems. In order to solve the bilevel programming model effectively, the outer and inner objective functions are first expressed as power functions, and then the bilevel programming problem is transformed into a relatively simple new problem by logarithmic transformation. Finally, the dual theory of linear programming is applied to transform the new bilevel problem into a single-layer nonlinear optimization problem and solve it. The computational results show that the results obtained by this method are more practical than those obtained by the existing methods.
【学位授予单位】：渤海大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：O221

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