一种新的局部时间积分的区域分解波形松弛算法

提出一种新的区域分解波形松弛算法, 使得可以在不同的子域采用不同的时间步长来并行求解线性抛物方程的初边值问题. 与传统的区域分解波形松弛算法相比, 该算法可以通过预条件子来加快收敛速度, 并且对内存的需求大大降低. 给出了局部时间步长一种具体的实现方法, 证明了离散解的存在唯一性, 并在时间连续水平分析了预条件系统. 数值实验显示了新算法的有效性.     

求解最大割问题的半定规划松驰的序列线性规划方法

本文基于最大割问题的半定规划松弛,利用矩阵分解的方法给出了与半定规划松弛等价的非线性规划模型,提出一种序列线性规划方法求解该模型.并在适当的条件下,证明了算法的全局收敛性.数值实验表明:序列线性规划方法在时间上要优于半定规划的内点算法.所以序列线性规划方法能更有效地求解大规模的最大割问题的半定规划松弛.     

平行机排序问题的列生成解法

基于整数规划的线性松弛,探讨求解大规模带权总完工时间排序问题的列生成算法的基本原理.然后,结合动态规划和分枝定界技术,对大规模排序问题P‖∑wiCj提出一类求解精确(最优)解的列生成算法.     

基于动态服务网络的铁路紧急输送计划编制模型和算法北大核心

根据特殊条件下铁路输送计划问题的动态性、多目标性、时效性等特点,采用时空网络构建铁路输送计划网络模型.并建立了基于动态路径的铁路输送计划编制数学模型.模型属于大规模的整数规划,以追求时间效益最大化和灾害损失最小化为目标.根据模型的特点,提出了松弛求解算法,借助LINGO求解工具求解松弛模型,通过逐步固定变量为整数值求得最优解.算例研究表明,算法可行有效.     

基于动态服务网络的铁路紧急输送计划编制模型和算法

根据特殊条件下铁路输送计划问题的动态性、多目标性、时效性等特点,采用时空网络构建铁路输送计划网络模型.并建立了基于动态路径的铁路输送计划编制数学模型.模型属于大规模的整数规划,以追求时间效益最大化和灾害损失最小化为目标.根据模型的特点,提出了松弛求解算法,借助LINGO求解工具求解松弛模型,通过逐步固定变量为整数值求得最优解.算例研究表明,算法可行有效.     

基于异步次梯度法的LR算法及其在多阶段HFSP的应用

为降低求解复杂度和缩短计算时间,针对多阶段混合流水车间总加权完成时间问题,提出了一种结合异步次梯度法的改进拉格朗日松弛算法。建立综合考虑有限等待时间和工件释放时间的整数规划数学模型,将异步次梯度法嵌入到拉格朗日松弛算法中,从而通过近似求解拉格朗日松弛问题得到一个合理的异步次梯度方向,沿此方向进行搜索,逐渐降低到最优点的距离。通过仿真实验,验证了所提算法的有效性。对比所提算法与传统的基于次梯度法的拉格朗日松弛算法,结果表明,就综合解的质量和计算效率而言,所提算法能在较短的计算时间内获得更好的近优解,尤其是对大规模问题。     

基于并行计算的多方向强次可行模松弛SQP算法

本文研究求解非线性约束优化问题.利用多方向并行方法,提出了一个新的强次可行模松弛序列二次规划(SQP)算法.数值试验表明,迭代次数和计算时间少于只取单一参数的传统算法.     

基于松弛策略解半无限规划模型的显式修正算法

讨论了一类线性半无限最优规划模型的求解算法.采用松弛方法解其系列子问题LP(T_k)及DLP(T_k),基于松弛策略和在适当的假设条件下,提出了一个我们称之为显式算法的新型算法.新算法的主要改进之处是算法在每一步迭代计算时,允许丢弃一些不必要的约束.在这种方式下,算法避免了求解系列太大规模的子问题.最后,基于提出的显式修正算法,并与传统割平面方法和已有文献中的松弛修正算法、对同一问题作了初步的数值比较实验.     

一类弱非线性方程组的非线性松弛非对称HSS类迭代算法

研究一类弱非线性方程组的求解问题,给出了求解此问题的一个非线性松弛非对称HSS类迭代算法,并在一定的条件下证明了算法的收敛性.数值结果表明该算法是有效的.     

工件优先级图为非连接图且含环的单机总加权拖期调度问题

为满足实际生产环境对工件加工顺序和工件到达时间的要求,提出了具有新特征的单机总加权拖期调度问题,其特点体现在:工件有动态到达时间,且由工件优先级关系构成的优先级图为非连接图且存在环的情况,对该问题建立数学规划模型,在扩展Tang和Xuan等的基础上,提出了结合双向动态规划的拉格朗日松弛算法求解该问题。在该算法的设计中,提出双向动态规划算法求解拉格朗日松弛问题,使得它可处理优先级图中一个工件可能有多个紧前或紧后工件的情况,采用次梯度算法更新拉格朗日乘子,基于拉格朗日松弛问题的解设计启发式算法构造可行解。实验测试结果显示,所设计的拉格朗日松弛算法能够在较短的运行时间内得到令人满意的近优解,为更复杂的调度问题的求解提供了思路。     

Spectral collocation and waveform relaxation methods for nonlinear delay partial differential equations

We investigate Chebyshev spectral collocation and waveform relaxation methods for nonlinear delay partial differential equations. Waveform relaxation methods allow to replace the system of nonlinear differential equations resulting from the application of spectral collocation methods by a sequence of linear problems which can be effectively integrated in a parallel computing environment by highly stable implicit methods. The effectiveness of this approach is illustrated by numerical experiments on the Hutchinson's equation. The boundedness of waveform relaxation iterations is proved for the Hutchinson's equation. This result is used in the proof of the superlinear convergence of the iterations.     

一类求解反应扩散方程的Newton波形松弛方法

对反应扩散方程提出一种新型的Newton波形松弛方法,并给出此方法的误差估计式.通过与传统的波形松弛方法比较,这种Newton波形松弛方法有更快的收敛性,且收敛速度不随网格加密而减慢.这种方法可以保持传统波形松弛方法可并行的特点.最后通过数值算例验证这种方法的有效性.     

An efficient algorithm for the parallel solution of high-dimensional differential equations

The study of high-dimensional differential equations is challenging and difficult due to the analytical and computational intractability. Here, we improve the speed of waveform relaxation (WR), a method to simulate high-dimensional differential-algebraic equations. This new method termed adaptive waveform relaxation (AWR) is tested on a communication network example. Further, we propose different heuristics for computing graph partitions tailored to adaptive waveform relaxation. We find that AWR coupled with appropriate graph partitioning methods provides a speedup by a factor between 3 and 16.     

Multigrid Waveform Relaxation for Anisotropic Partial Differential Equations

Multigrid waveform relaxation provides fast iterative methods for the solution of time-dependent partial differential equations. In this paper we consider anisotropic problems and extend multigrid methods developed for the stationary elliptic case to waveform relaxation methods for the time-dependent parabolic case. We study line-relaxation, semicoarsening and multiple semicoarsening multilevel methods. A two-grid Fourier–Laplace analysis is used to estimate the convergence of these methods for the rotated anisotropic diffusion equation. We treat both continuous time and discrete time algorithms. The results of the analysis are confirmed by numerical experiments.     

High performance parallel numerical methods for Volterra equations with weakly singular kernels

Non-stationary discrete time waveform relaxation methods for Abel systems of Volterra integral equations using fractional linear multistep formulae are introduced. Fully parallel discrete waveform relaxation methods having an optimal convergence rate are constructed. A significant expression of the error is proved, which allows us to estimate the number of iterations needed to satisfy a prescribed tolerance and allows us to identify the problems where the optimal methods offer the best performance. The numerical experiments confirm the theoretical expectations.     

Waveform relaxation: a convergence criterion for differential-algebraic equations

Numerical Algorithms - While waveform relaxation (also known as dynamic iteration or co-simulation) methods are known to converge for coupled systems of ordinary differential equations (ODEs), they...     

Continuous-time accelerated block successive overrelaxation methods for time-dependent Stokes equations

In order to solve the time-dependent Stokes equation, we follow the “Method of Lines” to obtain structured linear constant-coefficient differential–algebraic equations (DAEs). By taking advantage of the structure, we propose a class of waveform relaxation methods, called continuous-time accelerated block SOR (CABSOR) methods, for solving the obtained DAEs. The new methods are theoretically analyzed. The theory is applied to a two-dimensional time-dependent Stokes equation and verified by numerical experiments.     

Convergence of discrete time waveform relaxation methods

Numerical Algorithms - This paper concerns the discrete time waveform relaxation (DWR) methods for ordinary differential equations (ODEs). We present a general algorithm of constructing the DWR...     

Convergence analysis of waveform relaxation methods for neutral differential-functional systems

In this paper, the problems of convergence and superlinear convergence of continuous-time waveform relaxation method applied to Volterra type systems of neutral functional-differential equations are discussed. Under a Lipschitz condition with time- and delay-dependent right-hand side imposed on the so-called splitting function, more suitable conditions about convergence and superlinear convergence of continuous-time WR method are obtained. We also investigate the initial interval acceleration strategy for the practical implementation of the continuous-time waveform relaxation method, i.e., discrete-time waveform relaxation method. It is shown by numerical results that this strategy is efficacious and has the essential acceleration effect for the whole computation process.     

抛物型时间周期问题的Schwarz波形松驰方法

周期稳态是科学和工程系统中一类重要的运行状态,其计算复杂度远高于相应的初值问题,因此有更迫切的并行计算需要.我们提出了计算抛物型方程时间周期解的并行方法—基于区域分解(又称Schwarz方法)的波形松驰方法,该方法只需在子区域上求解较低维的周期问题.我们分析了两种不同的传输条件下方法的收敛性,并用数值实验支持了理论结果.