遗传算法用于电子枪发射系统的全局最优化设计

常用的优化设计方法，如单纯形法、Powell法等，易陷入局部最优解，而遗传算法是一种新兴的直接搜索最优化算法，它模拟达尔遗传选择与自然进化的理论，根据“适生存”和“优胜劣汰”的原则，借助“复制”、“交换”、“突变”等操作可以得到全局最优解，本将遗传算法运用于电子枪发射系统的最优化设计，得到了使交叠点半径尽可能小的发射系统的最佳结构和相应电参量。     

电子光学系统最优化设计中的非线性规划：应用与比较

以电子光学系统中发射系统为实例，从收敛速度，搜索效果，整体收敛性等几个方面，系统地对非线性规划的五种搜索方法在电子光学系统设计中的应用进行分析和比较，得出一些有价值的结果，计算表明Ｒｏｓｅｎｂｒｏｃｋ法是电子光学系统最优化设计中最值得推荐的方法。     

电子光学系统最优化设计中的科学计算可视化技术

在提出的电子光学系统最优化设计与科学计算可视化相结合的新构想－－可视化最优化设计中，以电子发射系统为例，提出了一种有效方法，逆向匹配插值法，可以将优化搜索过程中电子轨迹显示成电子束密度分布，进而为电子光学系统最优化设计实现实时控制和在线提供了可能性，还与类蒙特卡罗方法作了比较和讨论。     

电子光学系统最优化设计中的非线性规划:应用与比较

以电子光学系统中发射系统为实例，从收敛速度、搜索效果、整体收敛性等几个方面，系统地对非线性规划的五种搜索方法在电子光学系统设计中的应用进行分析和比较，得出了一些有价值的结果。计算表明Rosenbrock法是电子光学系统最优化设计中最值得推荐的方法。     

电子光学系统最优化设计中的科学计算可视化技术

在提出的电子光学系统最优化设计与科学计算可视化相结合的新构想──可视化最优化设计中，以电子发射系统为例，提出了一种有效方法：逆向匹配插值法，可以将代化搜索过程中电子轨迹显示成电子束密度分布，进而为电子光学系统最优化设计实现实时控制和在线判断提供了可能性。还与类蒙特卡罗方法作了比较和讨论。     

用于投射式电子束曝光系统的磁浸没透镜的优化设计

以磁浸没透镜的电流密度值的大小为优化参量,以成像系统的轴上像散为目标函数,利用单纯形优化法对用于投射式电子束曝光系统的新型磁浸没透镜进行了优化设计,结果表明,目标函数由未经优化前的358．187nm降低到50．693nm,同时单纯形优化法不需要已知目标函数与优化参量之间的解析关系式及求导,因此作为电子光学系统的最优化设计具有明显的优越性。     

遗传算法用于衍射光学元件的优化设计

提出了一种基于遗传算法的衍射光学元件优化设计方法;在衍射光学元件设计中遗传算法运行参数对遗传算法性能有一定的影响:采用较大的群体规模,遗传算法越容易获得最优解;交叉算子越大,遗传算法全局搜索能力越强;选择算子对遗传算法的影响不是太大;如果要进一步提高解的精度,可选取较大的终止代数。数值计算结果表明,用遗传算法优化设计的衍射光学元件,其误差小于 5.2%,衍射效率达到 91.2%。遗传算法很适合衍射光学元件的优化设计。     

给水管网管径优化设计的遗传算法

给水管网管径设计是离散变量的非线性优化问题，常规的数学规划方法采用连续变量求解，其最优解受初始值影响大。本文提出一种新方法－－遗传算法，它的特点在于：从多个初始点开始寻优，并采用交迭和变异算子避免过早地收敛到局部最优解，可获得全局最优解，且不受初始值影响。该算法不必求导计算，编程简单。     

基于遗传算法的板翅式换热器优化设计

以板翅式换热器的质量为目标函数,以换热器芯体外形尺寸和冷热两侧翅片参数为优化变量,分别采用改进遗传算法和基本遗传算法对其结构尺寸进行优化设计.结果表明,与原始数据相比,换热器的质量明显减小,同时证明改进遗传算法的有效性和先进性.     

基于遗传算法的散热器优化设计

根据电子设备散热装置缩小体积和增强散热性能的设计要求,分析散热器在强迫风冷条件下的散热性能优化问题。建立了热阻优化目标函数,采用遗传算法对强迫风冷情况下的散热器进行优化设计,计算出散热器的优化尺寸和优化前后的热阻,优化结果表明散热器体积和热阻可同时减小。     

Optimal Design of Alloy Steels Using Multiobjective Genetic Algorithms

Determining the optimal heat treatment regimen and the required weight percentages for the chemical composites to obtain the desired mechanical properties of steel is a challenging problem for the steel industry. To tackle what is in essence an optimization problem, several neural network-based models, which were developed in the early stage of this research work, are used to predict the mechanical properties of steel such as the tensile strength (TS), the reduction of area (ROA), and the elongation. Because these predictive models are generally data driven, such predictions should be treated carefully. In this research work, evolutionary multiobjective (EMO) optimization algorithms are exploited not only to obtain the targeted mechanical properties but also to consider the reliability of the predictions. To facilitate the implementation of a broad range of single-objective and multi-objective algorithms, a versatile Windows 2000®-based application is developed. The obtained results from the single-objective and the multiobjective optimization algorithms are presented and compared, and it is shown that the EMO techniques can be effectively used to deal with such optimization problems.     

一种混合优化策略在工步排序中的应用

结合创成式ＣＡＰＰ系统中工步优化问题，介绍了由遗传算法（ＧｅｎｅｔｉｃＡｌｇｏｒｉｔｈｍｓ，ＧＡ）和模拟退火算法（ＳｉｍｕｌａｔｅｄＡｎｎｅａｌｉｎｇＡｌｇｏｒｉｔｈｍｓ，ＳＡ）构成的混合寻优策略。最后以一箱体的工艺规划过程为例，将基于混合寻优策略的工步排序融入以加工中心为主要加工设备的ＣＡＰＰ工艺决策过程。     

Application of Genetic Algorithms in Texture Analysis and Optimization

The genetic algorithms method (GAM) is a modern computer technique based on some ideas taken from biological evolution theory. The GAM is especially useful in a study of problems being not completely determined. They are, e.g., problems having a few but not very different solutions or problems without a strict (exact) solution. The last situation may occur if it is enough to find a good enough solution but not necessarily the best one. In GAM approach, it is not necessary to know a priori a general scheme of problem solution; however, it is important to have a procedure estimating the quality of a solution. This procedure is necessary to eliminate some solutions and to accept another ones. In the last years, GAM was applied with success in different areas of science (e.g., sociology, construction engineering, artificial intelligence and many others). The present authors have applied GAM in crystallographic texture analysis: the orientation distribution function (ODF) was calculated from a set of measured pole figures. The quality of obtained results was very good; however, the calculation time and memory space were relatively high. The main reason of this situation was the use of spherical harmonic function series for the ODF representation. An important simplification of the calculation scheme (and of calculation time and memory space) can be obtained if ODF is represented by a sum of a few Gauss-type functions. The quality of solutions in this new approach is still very correct. The above-mentioned improved GAM scheme was also used to find an optimal crystallographic texture that optimizes the elastic properties of material. By using this approach the Young modulus can be maximised or minimised along a given sample direction.     

Eliminating Forging Defects Using Genetic Algorithms

In this article, an optimization method for metal forging process designs using finite element-based simulation is presented. Using as entry parameters the specifications of the final product the so-called inverse techniques developed for optimization problems allows the calculation of the optimal solution, the design parameters that produce the required product. An evolutionary genetic algorithm is proposed to calculate optimal shape geometry and temperature. An example demonstrating the efficiency of the developed method is presented considering a two-stage hot forging process. It considers optimization of the process parameters to reduce the difference between the realized and the prescribed final forged shape under minimal energy consumption, restricting the maximum temperature.     

一种基于遗传算法的光学薄膜优化设计方法

本文依据遗传算法的基本思想,立足光学薄膜领域,介绍了采用遗传算法进行光学薄膜设计优化的一种实现方法——包括"建立种群""建立适应度函数""选择""交叉""变异"和"精英保护"等方面的详细操作步骤.基于该方法,给出了一个在400 nm～900nm光谱区间内实现4个通带的优化设计实例,其结果表明该方法在膜系设计中能够起到较...     

Application of Genetic Algorithms to Geometry Optimization of Microclusters: A Comparative Study of Empirical Potential Energy Functions for Silicon

Evolutionary computation techniques (in particular, genetic algorithms) have been applied to optimize the structure of microclusters. Various empirical potential energy functions have been used to describe the interactions among the atoms in the clusters. A comparative study of silicon microclusters has been performed.     

遗传算法在水力管网优化中的应用

论述了遗传算法解决管网水力问题的主要步骤和优点,分析了遗传算法的结构和控制参数的选取。     

Evolutionary Design of Nickel-Based Superalloys Using Data-Driven Genetic Algorithms and Related Strategies

Data-driven models were constructed for the mechanical properties of multi-component Ni-based superalloys, based on systematically planned, limited experimental data using a number of evolutionary approaches. Novel alloy design was carried out by optimizing two conflicting requirements of maximizing tensile stress and time-to-rupture using a genetic algorithm-based multi-objective optimization method. The procedure resulted in a number of optimized alloys having superior properties. The results were corroborated by a rigorous thermodynamic analysis and the alloys found were further classified in terms of their expected levels of hardenabilty, creep, and corrosion resistances along with the two original objectives that were optimized. A number of hitherto unknown alloys with potential superior properties in terms of all the attributes ultimately emerged through these analyses. This work is focused on providing the experimentalists with linear correlations among the design variables and between the design variables and the desired properties, non-linear correlations (qualitative) between the design variables and the desired properties, and a quantitative measure of the effect of design variables on the desired properties. Pareto-optimized predictions obtained from various data-driven approaches were screened for thermodynamic equilibrium. The results were further classified for additional properties.     

城市导向系统设计中的视错觉

从城市建筑标志物缺少特色产生误导、道路与道路导向牌设计中的视错觉、导向中的色彩错觉等几个方面进行分析,提出导向设计中的一些误区与解决方案,希望能对城市导向系统设计有所帮助。