供应链环境下跨组织的PCPSP问题研究

在供应链环境下研究跨组织的资源受限项目调度问题,从项目调度整体效用最大化角度,考虑工期、成本和资源均衡对项目调度的影响。构建并剖析供应链环境下跨组织的资源受限项目调度模型,利用正态云模型中云滴的随机性与稳定性的特征改进遗传算法中交叉算子与变异算子的设置方式,并对模型进行数据模拟和算例分析。结果表明,以工期-成本-资源均衡为优化目标,不仅可实现供应链环境下跨组织的资源受限项目调度的效用最大化,且可缩短项目工期、降低成本并提高资源的利用率。     

列车与结构动态耦合分析的并行计算方法

在分析结构动态响应时考虑列车与结构的动态耦合作用,采用详细三维有限元模型会带来计算量太大的问题。本文采用并行计算方法,根据列车与结构动态耦合模型的计算特点,设计实现了列车结构耦合均衡的分区算法,并以两个工程应用为例,利用该方法对列车结构三维数值模型进行分区计算,结果表明该分区方法比递归坐标二分法有更好的并行效率。     

On Models of Nonlinear Evolution Paths in Adiabatic Quantum Algorithms

In this paper,we study two different nonlinear interpolating paths in adiabatic evolution algorithms for solving a particular class of quantum search problems where both the initial and final Hamiltonian are one-dimensional projector Hamiltonians on the corresponding ground state.If the overlap between the initial state and final state of the quantum system is not equal to zero,both of these models can provide a constant time speedup over the usual adiabatic algorithms by increasing some another corresponding "complexity".But when the initial state has a zero overlap with the solution state in the problem,the second model leads to an infinite time complexity of the algorithm for whatever interpolating functions being applied while the first one can still provide a constant running time.However,inspired by a related reference,a variant of the first model can be constructed which also fails for the problem when the overlap is exactly equal to zero if we want to make up the "intrinsic" fault of the second model - an increase in energy.Two concrete theorems are given to serve as explanations why neither of these two models can improve the usual adiabatic evolution algorithms for the phenomenon above.These just tell us what should be noted when using certain nonlinear evolution paths in adiabatic quantum algorithms for some special kind of problems.     

Multirate time stepping for accelerating explicit discontinuous Galerkin computations with application to geophysical flows

This paper presents multirate explicit time‐stepping schemes for solving partial differential equations with discontinuous Galerkin elements in the framework of Large‐scale marine flows. It addresses the variability of the local stable time steps by gathering the mesh elements in appropriate groups. The real challenge is to develop methods exhibiting mass conservation and consistency. Two multirate approaches, based on standard explicit Runge–Kutta methods, are analyzed. They are well suited and optimized for the discontinuous Galerkin framework. The significant speedups observed for the hydrodynamic application of the Great Barrier Reef confirm the theoretical expectations. Copyright © 2012 John Wiley & Sons, Ltd.     

The study of a two-phase wedge-sliding model on the ingredients drift of stable mixed fluid and its computing method

A two-phase wedge-sliding model is developed based on the micro-cellular structure and minimum entropy theory of stable system, and it is used to describe the ingredient distribution of mixed fluid in non-uniform stress field and to analyse its phase drift phenomenon. In the model, the drift-inhibition angle and the expansion-inhibition angle are also deduced and used as evaluating indexes to describe the drifting trend of different ingredients among the mixed fluids. For solving above two indexes of the model, a new calculation method is developed and used to compute the phase distributions of multiphase fluid at peak stress and gradient area stress respectively. As an example, the flow process of grease in a pipe is analysed by simulation method and used to verify the validity of the model.     

MATLAB中大型线性方程组的非定常迭代法

科学研究和大型工程设计中很多问题以非线性数学模型来描述,而这些数学模型求解常常归结为各种大型线性方程组的求解,因而能否有效地求解大型线性方程组,特别是病态的方程组,是非常关键的.本文介绍了MATLAB中求解大型线性方程组常用的非定常迭代法,并以GMRES算法为例介绍了算法的数学描述.     

Numerical approximation of conditional asymptotic variances using Monte Carlo simulation

We consider in this paper the use of Monte Carlo simulation to numerically approximate the asymptotic variance of an estimator of a population parameter. When the variance of an estimator does not exist in finite samples, the variance of its limiting distribution is often used for inferences. However, in this case, the numerical approximation of asymptotic variances is less straightforward, unless their analytical derivation is mathematically tractable. The method proposed does not assume the existence of variance in finite samples. If finite sample variance does exist, it provides a more efficient approximation than the one based on the convergence of finite sample variances. Furthermore, the results obtained will be potentially useful in evaluating and comparing different estimation procedures based on their asymptotic variances for various types of distributions. The method is also applicable in surveys where the sample size required to achieve a fixed margin of error is based on the asymptotic variance of the estimator. The proposed method can be routinely applied and alleviates the complex theoretical treatment usually associated with the analytical derivation of the asymptotic variance of an estimator which is often managed on a case by case basis. This is particularly appealing in view of the advance of modern computing technology. The proposed numerical approximation is based on the variances of a certain truncated statistic for two selected sample sizes, using a Richardson extrapolation type formulation. The variances of the truncated statistic for the two sample sizes are computed based on Monte Carlo simulations, and the theory for optimizing the computing resources is also given. The accuracy of the proposed method is numerically demonstrated in a classical errors-in-variables model where analytical results are available for the purpose of comparisons.     

The survival of the weakest in networks

We study here dynamic antagonism in a fixed network, represented as a graph G of n vertices. In particular, we consider the case of k≤n particles walking randomly independently around the network. Each particle belongs to exactly one of two antagonistic species, none of which can give birth to children. When two particles meet, they are engaged in a (sometimes mortal) local fight. The outcome of the fight depends on the species to which the particles belong. Our problem is to predict (i.e. to compute) the eventual chances of species survival. We prove here that this can indeed be done in expected polynomial time on the size of the network, provided that the network is undirected.

A high-fidelity approach for vehicle mobility simulation: Nonlinear finite element tires operating on granular material

Assessing the mobility of off-road vehicles is a complex task that most often falls back on semi-empirical approaches to quantifying the vehicle–terrain interaction. Herein, we concentrate on physics-based methodologies for wheeled vehicle mobility that factor in both tire flexibility and terrain deformation within a fully three-dimensional multibody system approach. We represent the tire based on the absolute nodal coordinate formulation (ANCF), a nonlinear finite element approach that captures multi-layered, orthotropic shell elements constrained to the wheel rim. The soil is modeled as a collection of discrete elements that interact through contact, friction, and cohesive forces. The resulting vehicle/tire/terrain interaction problem has several millions of degrees of freedom and is solved in an explicit co-simulation framework, built upon and now available in the open-source multi-physics package Chrono. The co-simulation infrastructure is developed using a Message Passing Interface (MPI) layer for inter-system communication and synchronization, with additional parallelism leveraged through a shared-memory paradigm. The formulation and software framework presented in this investigation are proposed for the analysis of the dynamics of off-road wheeled vehicle mobility. Its application is demonstrated by numerical sensitivity studies on available drawbar pull, terrain resistance, and sinkage with respect to parameters such as tire inflation pressure and soil cohesion. The influence of a rigid tire assumption on mobility is also discussed.     

Effects of water and ice clouds on cloud microphysical budget:An equilibrium modeling study

The effects of water and ice clouds on the cloud microphysical budget associated with rainfall are investigated through the analysis of grid-scale data from a series of two-dimensional cloud-resolving model equilibrium sensitivity simulations. The model is imposed without large-scale vertical velocity. In the control experiment, the contribution from rainfall （cM） associated with net evaporation and hydrometeor loss/convergence is about 29% of that from the rainfall （Cm） associated with net condensation and hydrometeor gain/divergence and about 39% of that from the rainfall （CM） associated with net condensation and hydrometeor loss/convergence. The exclusion of ice clouds enhances rainfall contribution of CM, whereas it reduces rainfall contributions of Cm and cM. The removal of radiative effects of water clouds increases rainfall contribution of CM, barely changes rainfall contribution of Cm and reduces the rainfall contribution of cM in the presence of the radiative effects of ice clouds. Elimination of the radiative effects of water clouds reduces the rainfall contributions of CM and Cm, whereas it increases the rainfall contribution of cM in the absence of the radiative effects of ice clouds.