Augmented Lagrangian Algorithms Based on the Spectral Projected Gradient Method for Solving Nonlinear Programming Problems

The spectral projected gradient method SPG is an algorithm for large-scale bound-constrained optimization introduced recently by Birgin, Martínez, and Raydan. It is based on the Raydan unconstrained generalization of the Barzilai-Borwein method for quadratics. The SPG algorithm turned out to be surprisingly effective for solving many large-scale minimization problems with box constraints. Therefore, it is natural to test its perfomance for solving the sub-problems that appear in nonlinear programming methods based on augmented Lagrangians. In this work, augmented Lagrangian methods which use SPG as the underlying convex-constraint solver are introduced (ALSPG) and the methods are tested in two sets of problems. First, a meaningful subset of large-scale nonlinearly constrained problems of the CUTE collection is solved and compared with the perfomance of LANCELOT. Second, a family of location problems in the minimax formulation is solved against the package FFSQP.     

Impact of Partial Separability on Large-Scale Optimization

ELSO is an environment for the solution oflarge-scale optimization problems. With ELSO the user is required to provide only code for the evaluation of a partially separable function. ELSO exploits the partialseparability structure of the function to computethe gradient efficiently using automatic differentiation.We demonstrate ELSO's efficiency by comparing thevarious options available in ELSO.Our conclusion is that the hybrid option in ELSOprovides performance comparable to the hand-coded option, while having the significantadvantage of not requiring a hand-coded gradient orthe sparsity pattern of the partially separable function.In our test problems, which have carefully coded gradients,the computing time for the hybrid AD option is within a factor of two of thehand-coded option.     

一类It型非线性时滞关联随机大系统的分散鲁棒控制

在非线性项满足全局Lipschitz条件下,本文研究了一类It型非线性时滞关联随机大系统的分散鲁棒控制问题.系统的时滞是关于状态和控制输入的.基于Lyapunov泛函及线性矩阵不等式(LMI)的分析方法,得到了无记忆状态反馈控制器使整个时滞关联随机大系统可镇定的充分条件.     

一类拟线性大系统的稳定性

本文应用大系统的分解方法和一个推广的不等式,研究了一类拟线性大系统的稳定性问题,所得结果简洁、易于验证,且推导过程不复杂,最后给出了应用实例。     

大规模界约束优化的子空间截断牛顿法

给出了大规模界约束优化的一个子空间截断牛顿法。利用截断牛顿法修正非有效约束所对应的变量，用投影梯度法修正有效约束所对应的变量，文中证明了方法的整体收敛性，并对方法进行了数值试验，且与子空间有限内存拟牛顿法进行了数值比较。     

采用自举技术的不完全绝热电路

为了大规模集成电路的低能耗应用,提出了一种不完全绝热电路——自举能量回收逻辑电路(bootstrapenergyrecoverylogic,BERL)。该电路采用二相无交叠功率时钟。由于采用自举技术,使负载的冲放电过程不会产生非绝热损失,并且输出开关的导通电阻变小,使绝热损失降低。为了比较BERL电路与静态CMOS电路及PAL-2n绝热电路的能耗,设计了反相器链电路。Hspice软件仿真结果表明,BERL电路的工作频率可以超过400MHz。在10～100MHz下,BERL能耗只有静态CMOS电路的25%～33%。相对于PAL-2n电路,BERL也有较低的能耗。在200MHz下,BERL能耗只有PAL-2n的50%。负载越重,BERL电路的低能耗优势越明显。     

迟后型时滞控制系统的稳定判断及稳定条件(下)

本文旨在把判断低阶时滞系统稳定性的“截点法”推广到高阶迟后型时滞系统的稳定性判断。文中具体分析了三阶时滞系统的稳定条件,并用计算机模拟证实了有关结论的正确性。此外,本文还提出了判断时滞系统不存在渐近稳定性质的基本理论及无渐近稳定的充分条件。     

On the generality of a cosmological speculation based on Heisenberg's principle

In a previous work [Hernández-Bermejo, B. (1996) Heisenberg's principle: A cosmological speculation, Speculations in Science and Technology, 19, 253], it was speculated that the lack of homogeneity of the large-scale structure of the universe may be due to quantum fluctuations of space in the early universe. This was argued for a Friedmann-type universe for which both the curvature and the cosmological constant were zero. Here it is shown that the same considerations are valid for arbitrary values of the curvature and .     

重叠结构分解与互联系统的控制性能

研究基于包含原理的大系统重叠结构分解方法对系统控制性能的影响.以两区域互联电力系统为例,在不同的重叠分解方法下,利用鲁棒镇定的LMI算法,对系统进行了控制仿真.研究表明,不同的重叠结构分解方法,使系统具有不同的动态性能和鲁棒性能,并且动态性能的鲁棒性能不可兼得,因此,在进行系统设计时应该折衷考虑.     

原初连续功率谱宇宙模型下暗物质晕的质量函数

最近的宇宙学观测结果给出了一个具有原初连续谱功率指数(RSI-CDM)的ΛCDM冷暗物质宇宙模型,而不是标准的尺度无关谱(PL-CDM).基于这个结果,应用半解析近似,对Jenkins et al(J01)质量方程进行了研究,同时在各个连续谱指数暗能量宇宙学模型下计算出这些模型对应的宇宙中最大暗物质晕的位里质量.结果表明,PL-CDM和RSI-CDM宇宙学模型在低红移处有微小差别.与PL-CDM相比, RSI-CDM在低红移处小质量暗晕的质量丰度较大,但在大结构质量晕中两者差别不明显, 而且这个差异随着红移降低而增大.RSI-CDM在高红移处压低了任何尺度的暗晕质量丰度.关于最大位里质量,平坦空间ΛCDM宇宙学模型在PL-CDM和RSI-CDM都给出更多大质量天体.因此,对PL-CDM和RSI-CDM功率谱模型,都可以用最大位里质量来区别不同的宇宙学模型.