The Sample Average Approximation Method Applied to Stochastic Routing Problems: A Computational Study

The sample average approximation (SAA) method is an approach for solving stochastic optimization problems by using Monte Carlo simulation. In this technique the expected objective function of the stochastic problem is approximated by a sample average estimate derived from a random sample. The resulting sample average approximating problem is then solved by deterministic optimization techniques. The process is repeated with different samples to obtain candidate solutions along with statistical estimates of their optimality gaps.We present a detailed computational study of the application of the SAA method to solve three classes of stochastic routing problems. These stochastic problems involve an extremely large number of scenarios and first-stage integer variables. For each of the three problem classes, we use decomposition and branch-and-cut to solve the approximating problem within the SAA scheme. Our computational results indicate that the proposed method is successful in solving problems with up to 2¹⁶⁹⁴ scenarios to within an estimated 1.0% of optimality. Furthermore, a surprising observation is that the number of optimality cuts required to solve the approximating problem to optimality does not significantly increase with the size of the sample. Therefore, the observed computation times needed to find optimal solutions to the approximating problems grow only linearly with the sample size. As a result, we are able to find provably near-optimal solutions to these difficult stochastic programs using only a moderate amount of computation time.     

Critical Point Theorems and Applications to Differential Equations

This paper contains a generalization of the well-known Palais-Smale and Cerami compactness conditions. The compactness condition introduced is used to prove some general existence theorems for critical points. Some applications are given to differential equations.     

Collaborative distributed decision making for large scale disaster relief operations: Drawing analogies from robust natural systems

One of the most ignored, but urgent and vital challenges confronting society today is the vulnerability of urban areas to extreme events. Current organization of response systems, predominantly based on a command and control model, limits their effectiveness and efficiency. Particularly, in decision‐making processes where a large number of actors may be involved. In this article, a new distributed collaborative decision‐making model is proposed to overcome command and control limitations encountered in stressful, hostile, chaotic, and large‐scale settings. This model was derived by borrowing concepts from the collective decision making of honeybees foraging, a successful process in solving complex tasks within complex settings. The model introduced in this article was evaluated through differential equations, i.e., continuous analysis, and difference equations, i.e., discrete analysis. The most important result found is that the best available option in any large‐scale decision‐making problem can be configured as an attractor, in a distributed and timely manner. We suggest that the proposed model has the potential to facilitate decision‐making processes in large‐scale settings. © 2005 Wiley Periodicals, Inc. Complexity 11:28–38, 2005     

二维椭圆型方程反问题中优化算法的比较

近年来，决定椭圆型方程系数反问题在地磁、地球物理、冶金和生物等实际问题上有着广泛的应用．本文讨论了二维的决定椭圆型方程系数反问题的数值求解方法．由误差平方和最小原则，这个反问题可化为一个变分问题，并进一步离散化为一个最优化问题，其目标函数依赖于要决定的方程系数．本文着重考察非线性共轭梯度法在此最优化问题数值计算中的表现，并与拟牛顿法作为对比．为了提高算法的效率我们适当选择加快收敛速度的预处理矩阵．同时还考察了线搜索方法的不同对优化算法的影响．数值实验的结果表明，非线性共轭梯度法在这类大规模优化问题中相对于拟牛顿法更有效．     

On the orthogonality of natural modes of vibration

The natural modes of a discrete linear system are orthogonal with respect to the mass and stiffness matrices in a generalized sense. However, these modes are usually not orthogonal to each other in the ordinary sense. The purpose of this paper is to document a number of conditions under which the modes are also orthogonal in an ordinary fashion.     

High-Power CO2 Laser System with Repetition Rate Operation for High Current Multicharged Heavy Ion Generations

Experimental and numerical calculation results devoted to development of an optical system for an ion source based on a repetition rate CO₂ laser are described. The laser chain consists of a master oscillator, gas absorber cells, and a four-pass amplifier. The optical system provides smooth laser pulses with variable duration and high spatial quality that ensures efficiency for plasma heating and ion generation. The parameters of the plasma ion component measured in the CERN laboratory are applied for a lead target illumination.     

Synthesis and characterization of oxidized cellulose

Samples of oxidized cellulose (OC) with various carboxyl contents and degrees of crystallinity were obtained by the oxidation of native and mercerized cellulose with a solution of nitrogen(IV) oxide in CCl₄. A detailed characterization of these OC samples was performed. The effect of oxidation conditions (concentration of N₂O₄ in the solution and oxidation time) and starting cellulose material on OC characteristics (carboxyl, carbonyl and nitrogen content, degree of crystallinity and polymerization, surface area and swelling, and acidic properties) was investigated. Reactivity in the oxidation process was higher in mercerized cellulose than in native cellulose. The action of dilute solutions (10–15%) of N₂O₄ did not affect the degree of crystallinity of cellulose samples. Under these conditions, the oxidation took place mainly in amorphous regions and on the surface of crystallites. Oxidation in a concentrated (40%) N₂O₄ solution led to the destruction of crystallites, which increased the surface area and swelling of cellulose in water. The surface area and the swelling of OC samples increased with a decrease in the index of crystallinity. The acidic properties of OC were shown to increase with an increase of swelling in water. © 2004 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 42: 4785–4791, 2004     

Reversible nonlinear conduction in high‐density polyethylene/acetylene carbon black composites at various ambient temperatures

The reversible nonlinear conduction (RNC) in of high‐density polyethylene/acetylene carbon black composites with different degrees of crosslinking was studied above room temperature and below the melting point of high‐density polyethylene (HDPE). The experimental current density‐electric field strength curves can be overlapped onto a master curve, suggesting that the microscopic mechanisms for the appearance of RNC exist regardless of the ambient temperature and the crosslinking degree of the HDPE matrix. The relationship between the crossover current density and the linear conductivity can be explained in the framework of the dynamic random‐resistor‐network model. According to these results, two electron‐tunneling models are suggested to interpret the microscopic conduction behavior. © 2004 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 42: 1212–1217, 2004     

对撞增强型YAG相位共轭腔

降低SBS相位共轭腔的启动阈值以及如何提高输出光束的质量一直是人们关心的课题。报道了在YAG激光器上运行一种新型对撞增强型YAG受激布里渊散射相位共轭激光腔的输出特性。该腔具有较低的启动阈值和较高的输出能量;该腔型最高能输出150mJ的能量,输出脉宽最窄为11ns,光束发散角为1.3mrad,输出能量和光束质量都很优良。