遗传算法及其在特种变压器优化设计中的应用研究
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摘要
特种变压器电磁参数的优化设计是一个带有等式和不等式约束,满足某种设计目标的非线性规划问题。本文对特种变压器电磁参数优化的数学模型的预处理、优化方法及软件体系结构框架等内容进行研究。
本文的主要研究工作如下:
1)建立特种变压器电磁参数优化设计的数学模型,提出了对它进行预处理的两种方法。一种是分段决策的处理方法,它将一个复杂的工程优化问题分解为若干简单的问题。另一种是对模型中目标函数、优化变量及约束因子进行规范化处理的方法。通过对特种变压器优化数学模型进行相应的预处理,方便了遗传算法的设计和实现,简化了优化过程,并使遗传算法的整体性能在较大程度上得到提高。
2)提出一种基于码表的动态编码的理论与方法。其基本思想是通过知识的指导,构建一种用于编码的参照表——码表;继而用动态与静态相结合的方法对变量进行编码。通过动态编码,有效地缩小了解的搜索空间,提高了最优解的质量,并在一定的程度上增强了编码的通用性。
3)提出一种新的遗传算子——培育算子。该算子使遗传操作能以较大的概率保持进化中表征优良特性的基因片段:使遗传操作朝最有希望获得最优解的方向进行。培育算子在算法执行的初期,能快速地提高个体的适应值,而在遗传操作的后期,对维持种群中个体的多样性有较大的贡献。
4)提出一种基于知识的自适应遗传算法(A Self-Adaptation Genetic
Optimization mathematical model of special transformer electromagnetism parameters is a nonlinear programming problem with equality and inequality constraints, to meet some certain design objective. In this thesis, preprocessing of the optimization mathematical model, optimization method and software framework of software architecture are studied.The main works of the thesis are summarized as follows:1) The optimization mathematical model for special transformer electromagnetism parameters is prospected, and two kinds methods of the preprocessing process for the above model are analyzed. One is section and decision making method, which solves the question of a complicated problem by dividing it into several simple problems. Another is a series of standardized treatment methods for the model components (i.e. objective function, optimization variables and constraints). Test result shows that the proposed preprocessing methods can improve the performance of the algorithm, simplify the optimization process, and the best solution quality gained is enhanced.2) A new construction method of dynamic encoding based on code table is presented. The key thought lies on constructing a referring encoding table (i.e., code table) using knowledge, and put forward a kind of collection dynamic and static characteristic encoding method. The search efficiency and the quality of
optimum solution can be enhanced, and the commonability of the code method has been strengthened on certain degree.3) A novel culture operator culture operator is proposed in genetic algorithm. The operator can preserve good characteristics genes in individuals at a higher probability, and genetic operator operation proceeds in the most promising direction. The individuals' fitness of population can be increased rapidly at the initial process of genetic operation, and the individuals' diversity in the population is maintained in the evolution procedure, which is particularly outstanding in the genetic operation's end process.4) A self-adaptation genetic algorithm based on knowledge (SAKGA) is proposed. The convergence of SAKGA is analyzed and proven. The optimization data show that SAKGA can produce performance improvement in execution time and accuracy, and it is potential to solve engineering optimization problems.5) A new software architecture framework is presented, and the software system of optimization design for special transformer is developed. The framework can separate electromagnetic parameters formulation and performance computation and simulation from the whole optimization process, guide the direction of optimization design by the peculiar adjustment mechanism in the system. Thus it can overcome non-linear coupling relation of parameter effectively in traditional software framework, which makes adjustment of parameter extremely difficult.
本文的主要研究工作如下:
1)建立特种变压器电磁参数优化设计的数学模型,提出了对它进行预处理的两种方法。一种是分段决策的处理方法,它将一个复杂的工程优化问题分解为若干简单的问题。另一种是对模型中目标函数、优化变量及约束因子进行规范化处理的方法。通过对特种变压器优化数学模型进行相应的预处理,方便了遗传算法的设计和实现,简化了优化过程,并使遗传算法的整体性能在较大程度上得到提高。
2)提出一种基于码表的动态编码的理论与方法。其基本思想是通过知识的指导,构建一种用于编码的参照表——码表;继而用动态与静态相结合的方法对变量进行编码。通过动态编码,有效地缩小了解的搜索空间,提高了最优解的质量,并在一定的程度上增强了编码的通用性。
3)提出一种新的遗传算子——培育算子。该算子使遗传操作能以较大的概率保持进化中表征优良特性的基因片段:使遗传操作朝最有希望获得最优解的方向进行。培育算子在算法执行的初期,能快速地提高个体的适应值,而在遗传操作的后期,对维持种群中个体的多样性有较大的贡献。
4)提出一种基于知识的自适应遗传算法(A Self-Adaptation Genetic
Optimization mathematical model of special transformer electromagnetism parameters is a nonlinear programming problem with equality and inequality constraints, to meet some certain design objective. In this thesis, preprocessing of the optimization mathematical model, optimization method and software framework of software architecture are studied.The main works of the thesis are summarized as follows:1) The optimization mathematical model for special transformer electromagnetism parameters is prospected, and two kinds methods of the preprocessing process for the above model are analyzed. One is section and decision making method, which solves the question of a complicated problem by dividing it into several simple problems. Another is a series of standardized treatment methods for the model components (i.e. objective function, optimization variables and constraints). Test result shows that the proposed preprocessing methods can improve the performance of the algorithm, simplify the optimization process, and the best solution quality gained is enhanced.2) A new construction method of dynamic encoding based on code table is presented. The key thought lies on constructing a referring encoding table (i.e., code table) using knowledge, and put forward a kind of collection dynamic and static characteristic encoding method. The search efficiency and the quality of
optimum solution can be enhanced, and the commonability of the code method has been strengthened on certain degree.3) A novel culture operator culture operator is proposed in genetic algorithm. The operator can preserve good characteristics genes in individuals at a higher probability, and genetic operator operation proceeds in the most promising direction. The individuals' fitness of population can be increased rapidly at the initial process of genetic operation, and the individuals' diversity in the population is maintained in the evolution procedure, which is particularly outstanding in the genetic operation's end process.4) A self-adaptation genetic algorithm based on knowledge (SAKGA) is proposed. The convergence of SAKGA is analyzed and proven. The optimization data show that SAKGA can produce performance improvement in execution time and accuracy, and it is potential to solve engineering optimization problems.5) A new software architecture framework is presented, and the software system of optimization design for special transformer is developed. The framework can separate electromagnetic parameters formulation and performance computation and simulation from the whole optimization process, guide the direction of optimization design by the peculiar adjustment mechanism in the system. Thus it can overcome non-linear coupling relation of parameter effectively in traditional software framework, which makes adjustment of parameter extremely difficult.
引文
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