连续位相板设计质量的评价方法

鉴于 GS算法设计得到的连续位相板具有面形复杂、加工困难的特征,提出了同时使用面形及焦斑参数对其进行评价的方法。根据实际设计结果计算了相位板峰谷值和均方根值以及对应的焦斑特性,分析了峰谷值和均方根值作为评价参数的可行性。最后对比三组不同位相板对应的焦斑,分析了焦斑的 PV值,RMS值以及其功率谱密度。     

位相型衍射光学元件设计的混合算法

针对传统的光束整形算法在设计位相型衍射光学元件时效果差的缺点,本文提出了一种适合于位相型衍射光学元件设计的新混合算法.该混合算法是将变尺度BFGS算法融入遗传算法中,其中变尺度BFGS算法主要用于局部搜索,同时将罚函数优化准则用于成本函数的构造中.相比于传统的优化算法,该混合算法具有效率高、收敛快和稳定性好等优点.作为一个设计实例,我们分别将传统模拟退火算法和该混合算法应用到高斯光束整形中,进行了数值模拟,为了考察该混合算法的可靠性,设定了衍射效率和信噪比两个技术指标.设计结果表明:该混合算法收敛速度快,设计效费比优,仅需少量的迭代次数就能达到高衍射效率和高信噪比的要求.用该混合算法设计的衍射光学元件,能极大地改善整形效果,在均匀性要求较高的场合有广泛的应用前景.     

离子束刻蚀工艺误差对DOE器件的影响

针对衍射光学元件(DOE)的离子束刻蚀工艺,结合掩模套刻过程实例,本文提出了刻蚀误差面形分布的概念.在标量衍射的夫琅和费原理上,进行了误差数值模拟分析及讨论.模拟分析和实验数据结果表明,误差的面形分布在DOE器件的衍射焦斑中心会产生一个明显的光强畸变毛刺亮点,严重破坏了靶场照明的均匀性.     

基于免疫遗传算法的二元光学元件的位相设计

在激光诱导扩散中,需要利用二元光学元件对激光器输出的高斯光束进行整形,以实现曝光区的温度分布均匀化。为了得到二元光学元件的位相分布,采用免疫遗传对相位分布进行设计。免疫遗传算法中采取变频率的交叉操作、变异操作,克服了遗传算法在局部搜索解空间上效率差的缺点,并使算法跳出局部极大值的能力得到了增强。采取由正向记忆细胞库提取的免疫疫苗对抗体群进行接种,使群体的进化方向得到引导,提高了算法的进化效率;采取由反向记忆细胞库提取的劣化疫苗对抗体群进行反向接种,减少算法的重复运算,极大地抑制了群体退化;采用B、T细胞的作用机制,保持群体在进化过程中的多样性,很大程度上抑制了算法未成熟收敛。运算结果表明,免疫遗传算法较遗传算法具有更高的算法效率和更强的寻优能力。最后考虑到实际加工,对最优解做适当调整得到了更适合于实际加工的二元光学元件的位相分布。     

二元光学元件的耦合波分析

基于Ｍａｘｗｅｌｌ方程和电磁场的边界连续条件，本文导出了二元光学器件的严格的耦合波方程，指出各级次衍射波之间存在着相互耦合波衍射理论对元元位相光栅的衍射特性进行了分析，并与标量衍射理论分析的结果作了比较，从而得出了一些重要的结论。     

位相型自聚焦微分滤波器

介绍一种用二元光学方法制作的光学图象微分滤波器，它是由两个频率相近的位相型Ｒｏｎｃｈｉ光栅和离轴型位相菲涅耳波带片的组合而成的。称之为位相型自聚焦滤波器。它具有衍射效率高，光路简单，使用方便等特点。     

基于混合暗通道算法的图像去雾研究

基于混合暗通道算法对图像去雾进行了研究。首先通过阈值划分混合暗通道,混合暗通道为近景区域和远景区域之和,最大化相似度评价函数获得混合暗通道微调系数;接着通过像素点与区域中心点的暗通道光强差值实现近景区域去雾,远景区域去雾规则是通过像素的膨胀、腐蚀实现;最后给出了算法流程。实验仿真显示该算法去雾图像视觉比其它算法的效果好,定量分析指标较优。     

直接二元搜索法合成二元位相计算全息图

提出了用递归直接二元搜索算法（ＤＢＳ）设计二元位相计算全息图的新方法，分析了ＤＢＳ型位相计算全息图的设计原理，计算机模拟定量地分析恢复象的质量和衍射效率，分析结果表明该位相计算全息图恢复象质量较好、衍射效率高，在光电技术、光学信息处理等领域中有重要的应用前景     

抛物面型X射线组合折射透镜光学性能分析

抛物面型X射线组合折射透镜是一种适用于硬X射线波段的新型光学元件.由于采用抛物面型,可以消除球差,因而能够产生亚微米尺度焦斑并具有更好的成像性能.本文给出了旋转轴对称抛物面型X射线组合透镜的理论研究成果.首先,利用矩阵光学方法,推导了其精确的焦距公式,得到了薄透镜判定准则;其次,根据衍射理论,推导出焦点处的光强分布,得到其极限焦斑大小.最后,本文还给出了透过率和有效孔径的理论公式.针对用Al、Be、PMMA三种材料制作的抛物面型X射线组合折射透镜,本文给出了各个光学性能指标的数值计算沣结果.     

基于成像球光强测量系统的光学设计

提出一种新的快速测量空间光强分布的方法,完成基于该方法测量系统的光学系统设计,并对光学系统的关键器件进行设计.利用Matlab编程和Solidworks三维建模得到自由曲面反射镜面型,Zemax光学软件设计优化得到双高斯物镜.光线追踪仿真软件LightTools对测量系统进行模拟仿真,验证系统的可行性,并对该构架下测量系统最小角分辨率和动态范围的关键性能指标进行分析.结果表明,设计的基于成像球的测量系统可实现空间光强分布测量.     

Comparison of simulated quenching algorithms for design of diffractive optical elements

We compare the performance of very fast simulated quenching; generalized simulated quenching, which unifies classical Boltzmann simulated quenching and Cauchy fast simulated quenching; and variable step size simulated quenching. The comparison is carried out by applying these algorithms to the design of diffractive optical elements for beam shaping of monochromatic, spatially incoherent light to a tightly focused image spot, whose central lobe should be smaller than the geometrical-optics limit. For generalized simulated quenching we choose values of visiting and acceptance shape parameters recommended by other investigators and use both a one-dimensional and a multidimensional Tsallis random number generator. We find that, under our test conditions, variable step size simulated quenching, which generates each parameter's new states based on the acceptance ratio instead of a certain theoretical probability distribution, produces the best results. Finally, we demonstrate experimentally a tightly focused image spot, with a central lobe 0.22-0.68 times the geometrical-optics limit and a relative sidelobe intensity 55%-60% that of the central maximum intensity.     

Changes of intensity distribution of a tightly focused plane-wave pulse induced by lens dispersion

The tightly focusing properties of a linearly polarized plane-wave pulse through a high numerical aperture (NA) lens with dispersion are formulated. The effects of lens dispersion on the tightly focused intensity distribution in the focal region are studied in detail. It is found that, because of the lens dispersion, the intensity of the side lobe of the focused light spot strengthens in the transverse direction and the size of the main lobe of the focused light spot increases in the longitudinal direction as the pulse duration decreases. In addition, we compare the effects of dispersion of lens made by different types of glass on tightly focusing properties of a pulse beam. The results will be helpful to choose suitable high NA objective lens in experiment.     

Scheduling job shop problems with sequence-dependent setup times

In this work we consider job shop problems where the setup times are sequence dependent under minimisation of the maximum completion time or makespan. We present a genetic algorithm to solve the problem. The genetic algorithm is hybridised with a diversification mechanism, namely the restart phase, and a simple form of local search to enrich the algorithm. Various operators and parameters of the genetic algorithm are reviewed to calibrate the algorithm by means of the Taguchi method. For the evaluation of the proposed hybrid algorithm, it is compared against existing algorithms through a benchmark. All the results demonstrate that our hybrid genetic algorithm is very effective for the problem.     

Single Failure Routing Protection Algorithm in the Hybrid SDN Network

Loop free alternate (LFA) is a routing protection scheme that is currently deployed in commercial routers. However, LFA cannot handle all single network component failure scenarios in traditional networks. As Internet service providers have begun to deploy software defined network (SDN) technology, the Internet will be in a hybrid SDN network where traditional and SDN devices coexist for a long time. Therefore, this study aims to deploy the LFA scheme in hybrid SDN network architecture to handle all possible single network component failure scenarios. First, the deployment of LFA scheme in a hybrid SDN network is described as a 0-1 integer linear programming (ILP) problem. Then, two greedy algorithms, namely, greedy algorithm for LFA based on hybrid SDN (GALFAHSDN) and improved greedy algorithm for LFA based on hybrid SDN (IGALFAHSDN), are proposed to solve the proposed problem. Finally, both algorithms are tested in the simulation environment and the real platform. Experiment results show that GALFAHSDN and IGALFAHSDN can cope with all single network component failure scenarios when only a small number of nodes are upgraded to SDN nodes. The path stretch of the two algorithms is less than 1.36.     

Two efficient algorithms for constructing almost even approximations of the Pareto front in multi-objective optimization problems

In this article, two algorithms are proposed for constructing almost even approximations of the Pareto front of multi-objective optimization problems. The first algorithm is a hybrid of the ε-constraint and Pascoletti–Serafini scalarization methods for solving bi-objective problems. The second is a modification of the successive Pareto optimization (SPO) algorithm for solving three-objective problems. In these algorithms, the MATLAB fmincon solver is used to solve single-objective optimization problems, which returns a local optimal solution. Some metrics are considered to evaluate the quality of approximations obtained by the suggested algorithms on six test problems, and their results are compared with other algorithms (normal constraint, weighted constraint, SPO, differential evolution, multi-objective evolutionary algorithm/decomposition–differential evolution, non-dominated sorting genetic algorithm-II and S-metric selection evolutionary multi-objective algorithm). Experimental results show that the proposed algorithms provide almost even approximations of the whole Pareto front, and better quality of approximation and CPU time compared with established algorithms.     

Threshold automatic selection hybrid phase unwrapping algorithm for digital holographic microscopy

Conventional quality-guided (QG) phase unwrapping algorithm is hard to be applied to digital holographic microscopy because of the long execution time. In this paper, we present a threshold automatic selection hybrid phase unwrapping algorithm that combines the existing QG algorithm and the flood-filled (FF) algorithm to solve this problem. The original wrapped phase map is divided into high- and low-quality sub-maps by selecting a threshold automatically, and then the FF and QG unwrapping algorithms are used in each level to unwrap the phase, respectively. The feasibility of the proposed method is proved by experimental results, and the execution speed is shown to be much faster than that of the original QG unwrapping algorithm.     

基于混合遗传算法的多箱型三维装箱问题研究

目的 提高电商仓储领域打包环节包装箱的利用率。方法 针对电商仓储领域多箱型多种物品类型的三维装箱问题,建立混合整数规划的数学模型,设计基于启发式经验规则和多种算子组合的装箱过程模块算法。分别从装箱顺序和带有改进型算子这两方面设计多箱型三维装箱问题混合遗传算法,对装箱方案进行优化。结果 经实验证明,在装箱顺序优化环节PSO–HGA算法系列中,PSO–HGA–S1算法最优。在带有改进算子的混合遗传算法中,IPO–HGA–S1算法最优。结论 文中设计的混合遗传算法能很好地提高电商仓储领域打包环节包装箱的利用率。     

A particle swarm optimization algorithm for hybrid flow-shop scheduling with multiprocessor tasks

The multistage hybrid flow-shop scheduling problem with multiprocessor tasks has been found in many practical situations. Due to the essential complexity of the problem, many researchers started to apply metaheuristics to solve the problem. In this paper, we address the problem by using particle swarm optimization (PSO), a novel metaheuristic inspired by the flocking behaviour of birds. The proposed PSO algorithm has several features, such as a new encoding scheme, an implementation of the best velocity equation and neighbourhood topology among several different variants, and an effective incorporation of local search. To verify the PSO algorithm, computational experiments are conducted to make a comparison with two existing genetic algorithms (GAs) and an ant colony system (ACS) algorithm based on the same benchmark problems. The results show that the proposed PSO algorithm outperforms all the existing algorithms for the considered problem.