基于整体退火遗传算法的膜系设计方法

提出了以遗传算法和模拟退火算法相结合的整体退火遗传算法（ＧＡＳＡ）进行膜系设计的新方法。整体退火遗传算法具有全局寻优能力,与作为现代光学薄膜自动设计的主要方法－针法相比,在相同薄膜层数情况下用该方法设计可以得到较优的结果,或者用更少的薄膜层数达到同样的设计结果。并且对初始条件不敏感,可以确定膜层厚度边界,以确保制备方便。理论与实例表明该方法是高效的和可靠的。     

遗传算法在窄带滤光片膜系设计中的应用

研究了遗传算法在窄带滤光片膜系设计中的应用。介绍了遗传算法的运算原理、适应度函数和运行参数的涵义;建立了窄带滤光片的评价函数和适应度函数,并给出其遗传算法的程序设计方法;以带宽4nm、中心波长1.55μm的窄带滤光片为例进行了遗传算法的实际膜系设计。结果表明遗传算法适用窄带滤光片的膜系设计。     

基于进化算法的产品造型创新设计方法研究

为了满足用户多样化的产品造型需求,模拟设计师的设计思维特性,提出了应用元胞遗传算法和标准遗传算法的产品造型创新设计新方法.首先收集产品样本,经聚类分析、设计师聚焦等确定代表性产品样本,再利用形态分析法得到产品造型元素并定量描述设计参数;其次,以代表性产品样本为初始种群,应用元胞遗传算法建立产品造型初始设计系统,实现了以少量原型生成大量创新性方案的智能设计进程;最后,应用标准遗传算法建立产品造型细化设计系统,进一步优化初始设计方案,快速实现方案的细化智能设计进程.卡通表情造型设计实例表明,该方法可为创新设计提供有效的辅助与支持.     

多层薄膜光学常数的椭偏法研究

研究了椭偏测量中多层薄膜拟和模型建立的过程,并对一未知多层光学薄膜进行了椭偏分析,建立了substrate/film1/EMA/film2/srough的物理结构模型.采用椭偏法,在首先确定出基底光学常数的基础上,提出了从单层、双层、三层逐次建模拟和的分析方法.研究结果表明:对于透明或弱吸收光学薄膜,采用柯西公式可以较好表征材料的色散关系.椭偏分析最终得到的未知薄膜基本结构为G(1.52)/2.0312(203.0 nm)1.4636(170.1 nm)2.079 1(170.4 nm)/A,膜系设计及分光光度计测量的透射光谱证实了这一结果.对多层膜厚度和光学常数的分析表明,椭偏法仍然是一种行之有效的薄膜光学常数测量方法.     

大规模物流网络的组合遗传算法研究

在对遗传算法、生成树遗传算法和混合进化方法进行比较的基础上,提出组合遗传算法来解决大规模基本物流网络设计问题.该问题抽象为"选址-分派问题",并进一步分解,且将"分派"镶嵌在"选址"中."选址"和"分派"染色体分别使用二进制编码和矩阵编码、适值采用物流费用.运算结果显示该方法比混合进化方法结果更精确,且在大规模问题求解方面速度优于通常的遗传算法,因此是一种设计大规模物流网络的较好方法.     

光学薄膜的数字滤波器设计方法

本文给出利用数字滤波器的设计方法设计光学薄膜的具体过程.由数字滤波器设计软件,按照光学薄膜的设计要求给出光学薄膜目标谱传递函数,将光学薄膜传榆矩阵表示为格型数字滤波器传输矩阵的数学形式,导出等光学厚度光学薄膜传递函数的递归关系式.利用光学薄膜传递函数递归关系,采用剥层算法计算出各膜层的折射率,得到满足目标谱传递函数的膜...     

光纤通信系统用减反膜的研究

针对WDM光纤通信系统对具有极高透过率的光学薄膜元件的需要，系统地研究了增透膜的设计与镀制．采用统计实验求总极值法和Powell最小二乘法相结合的多级优化方法编制程序，完成了以BK，玻璃为基底的增透膜的膜系设计，采用多种监控方法完成了此类非规整膜系的镀制实验．测试结果表明，采用变过正量极值法监控非规整膜系的镀制，可精确控制各层膜的光学厚度，获得在1550nm波段附近具有很高透过率的光学薄膜元件．     

基于遗传算法的车辆用空调换热器的优化

针对轿车空调用冷凝器的特点,在平行流冷凝器数学模型的基础上,建立了综合考虑换热器体积和阻力的性能评价因子,并将遗传算法引入平行流冷凝器的结构优化中,该方法通过将冷凝器的结构参数转化为遗传算法中染色体,通过种群进化实现换热器结构的优化.最后对实际车型冷凝器的计算,达到了较好的设计结果.     

基于遗传算法的车辆用空调换热器的优化

针对轿车空调用冷凝器的特点,在平行流冷凝器数学模型的基础上,建立了综合考虑换热器体积和阻力的性能评价因子,并将遗传算法引入平行流冷凝器的结构优化中,该方法通过将冷凝器的结构参数转化为遗传算法中染色体,通过种群进化实现换热器结构的优化.最后对实际车型冷凝器的计算,达到了较好的设计结果.     

一种并行遗传算法在家纺企业车间调度的应用

针对家纺企业受特殊工艺约束的车间调度问题,提出了一个基于向量组编码的新的遗传算法,并设计了EOX交叉和启发式变异方法.在基于遗传算法自然并行性特点的基础上,实现了主从式控制网络模式下并行遗传算法.通过仿真实验证明,建立的算法是有效的,收敛速度快,具有较高的并行性,优于普通的遗传算法.     

Optimal Building Frame Column Design Based on the Genetic Algorithm

Building structure is like the skeleton of the building, it bears the effects of various forces and forms a supporting system, which is the material basis on which the building depends. Hence building structure design is a vital part in architecture design, architects often explore novel applications of their technologies for building structure innovation. However, such searches relied on experiences, expertise or gut feeling. In this paper, a new design method for the optimal building frame column design based on the genetic algorithm is proposed. First of all, in order to construct the optimal model of the building frame column, building units are divided into three categories in general: building bottom, main building and building roof. Secondly, the genetic algorithm is introduced to optimize the building frame column. In the meantime, a PGA-Skeleton based concurrent genetic algorithm design plan is proposed to improve the optimization efficiency of the genetic algorithm. Finally, effectiveness of the mentioned algorithm is verified through the simulation experiment.     

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。     

Design of code division multiple access filters based on sampled fiber Bragg grating by using global optimization algorithms

In this article, we focus on the design of code division multiple access filters (used in data transmission) composed of a particular optical fiber called sampled fiber Bragg grating (SFBG). More precisely, we consider an inverse problem that consists in determining the effective refractive index profile of an SFBG that produces a given reflected spectrum. In order to solve this problem, we use an original multi-layers semi-deterministic global optimization method based on the search of suitable initial conditions for a given optimization algorithm. The results obtained with our optimization algorithms are compared, in term of complexity and final design, with those given by an hybrid genetic algorithm (the method generally considered in the literature for designing SFBGs).     

离散变量结构优化设计的拟满应力遗传算法

以力学准则法为基础,提出了一种求解离散变量结构优化设计的拟满应力方法;这种方法能直接求解具有应力约束和几何约束的离散变量结构优化设计问题。通过在遗传算法中定义拟满应力算子,建立了一种离散变量结构优化设计的混合遗传算法拟满应力遗传算法。算例表明:这种混合遗传算法对于离散变量结构优化设计问题具有较高的计算效率。     

Optical coating design algorithm based on the equivalent layers theory

New optical coating design algorithm with the equivalent layers theory is presented. The algorithm is based on the merit-function-constrained optimization in the accessible domain of equivalent phase thicknesses and equivalent refractive indices. It allows for creation of design coatings with sophisticated narrowband spectral characteristics. (     

Global optimization and modeling techniques for planar multilayered dielectric structures

We present a multilevel global optimization strategy for synthesizing planar multilayered dielectric structures. A low discrepancy sequence of sample points with uniform variable space coverage allows a global-level search while systematic refinement using gradient-based techniques identifies optima at the local level. Since efficient local optimization is important for this method, a fast calculation approach based on mode matching is presented; this also facilitates the compact derivation of analytical gradients. The approach is compared with genetic and simulated annealing algorithms through an antireflection coating design. The method proves to be competitive in terms of its performance, nonadaptive algorithm, and ability to track local solutions.     

Genetic local search algorithm for optimization design of diffractive optical elements

We propose a genetic local search algorithm (GLSA) for the optimization design of diffractive optical elements (DOE's). This hybrid algorithm incorporates advantages of both genetic algorithm (GA) and local search techniques. It appears better able to locate the global minimum compared with a canonical GA. Sample cases investigated here include the optimization design of binary-phase Dammann gratings, continuous surface-relief grating array generators, and a uniform top-hat focal plane intensity profile generator. Two GLSA's whose incorporated local search techniques are the hill-climbing method and the simulated annealing algorithm are investigated. Numerical experimental results demonstrate that the proposed algorithm is highly efficient and robust. DOE's that have high diffraction efficiency and excellent uniformity can be achieved by use of the algorithm we propose.     

Solving Job-Shop Scheduling Problems by Genetic Algorithms Based on Building Block Hypothesis

In this paper, we propose a new genetic algorithm for job-shop scheduling problems （JSP）. The proposed method uses the operation-based representation, based on schema theorem and building block hypothesis, a new crossover is proposed ： By selecting short, low order highly fit schemas to genetic operator, the crossover can exchange meaningful ordering information of parents effectively and can search the global optimization. Simulation results on MT benchmark problem coded by C ＋ ＋ show that our genetic operators are very powerful and suitable to job-shop scheduling problems and our method outperforms the previous GA-based approaches.