Based on the fact that a static problem has an equivalent wave speed of infinity and a dynamic problem has a wave speed of finite value, an effective loading algorithm associated with the explicit dynamic relaxation m...Based on the fact that a static problem has an equivalent wave speed of infinity and a dynamic problem has a wave speed of finite value, an effective loading algorithm associated with the explicit dynamic relaxation method was presented to produce meaningful numerical solutions for static problems. The central part of the explicit dynamic relaxation method is to turn a time-independent static problem into an artificial time-dependent dynamic problem. The related numerical testing results demonstrate that: (1) the proposed effective loading algorithm is capable of enabling an applied load in a static problem to be propagated throughout the whole system within a given loading increment, so that the time-independent solution of the static problem can be obtained; (2) the proposed effective loading algorithm can be straightforwardly applied to the particle simulation method for solving a wide range of static problems.展开更多
In this paper, an absorbing Fictitious Boundary Condition (FBC) is presented to generate an iterative Domain Decomposition Method (DDM) for analyzing waveguide problems.The relaxed algorithm is introduced to improve t...In this paper, an absorbing Fictitious Boundary Condition (FBC) is presented to generate an iterative Domain Decomposition Method (DDM) for analyzing waveguide problems.The relaxed algorithm is introduced to improve the iterative convergence. And the matrix equations are solved using the multifrontal algorithm. The resulting CPU time is greatly reduced.Finally, a number of numerical examples are given to illustrate its accuracy and efficiency.展开更多
A class of nonidentical parallel machine scheduling problems are considered in which the goal is to minimize the total weighted completion time.Models and relaxations are collected.Most of these problems are NP-hard,i...A class of nonidentical parallel machine scheduling problems are considered in which the goal is to minimize the total weighted completion time.Models and relaxations are collected.Most of these problems are NP-hard,in the strong sense,or open problems,therefore approximation algorithms are studied.The review reveals that there exist some potential areas worthy of further research.展开更多
In this paper, a new method, so called A-method, is given for the convergence analysis of the MQ-algorithm. And the finer relaxation parameter θA is obtained. The numerical results show that our new method has the ou...In this paper, a new method, so called A-method, is given for the convergence analysis of the MQ-algorithm. And the finer relaxation parameter θA is obtained. The numerical results show that our new method has the outstanding effect of accelerating convergence. Moreover, the relaxation parameter θA is the optimum in a point of view.展开更多
In this paper,we establish a new algorithm to the non-overlapping Schwarz domain decomposition methods with changing transmission conditions for solving one dimensional advection reaction diffusion problem.More precis...In this paper,we establish a new algorithm to the non-overlapping Schwarz domain decomposition methods with changing transmission conditions for solving one dimensional advection reaction diffusion problem.More precisely,we first describe the new algorithm and prove the convergence results under several natural assumptions on the sequences of parameters which determine the transmission conditions.Then we give a simple method to estimate the new value of parameters in each iteration.The interesting advantage of our method is that one may update the better parameters in each iteration to save the computational cost for optimizing the parameters after many steps.Finally some numerical experiments are performed to show the behavior of the convergence rate for the new method.展开更多
The multisplitting algorithm for solving large systems of ordinary differential equations on parallel computers was introduced by Jeltsch and Pohl in [1]. On fixed time intervals conver gence results could be derived ...The multisplitting algorithm for solving large systems of ordinary differential equations on parallel computers was introduced by Jeltsch and Pohl in [1]. On fixed time intervals conver gence results could be derived if the subsystems are solving exactly.Firstly,in theis paper,we deal with an extension of the waveform relaxation algorithm by us ing multisplittin AOR method based on an overlapping block decomposition. We restricted our selves to equidistant timepoints and dealed with the case that an implicit integration method was used to solve the subsystems numerically in parallel. Then we have proved convergence of multi splitting AOR waveform relaxation algorithm on a fixed window containing a finite number of timepoints.展开更多
The multiple knapsack problem denoted by MKP (B,S,m,n) can be defined as fol- lows.A set B of n items and a set Sof m knapsacks are given such thateach item j has a profit pjand weightwj,and each knapsack i has a capa...The multiple knapsack problem denoted by MKP (B,S,m,n) can be defined as fol- lows.A set B of n items and a set Sof m knapsacks are given such thateach item j has a profit pjand weightwj,and each knapsack i has a capacity Ci.The goal is to find a subset of items of maximum profit such that they have a feasible packing in the knapsacks.MKP(B,S,m,n) is strongly NP- Complete and no polynomial- time approximation algorithm can have an approxima- tion ratio better than0 .5 .In the last ten years,semi- definite programming has been empolyed to solve some combinatorial problems successfully.This paper firstly presents a semi- definite re- laxation algorithm (MKPS) for MKP (B,S,m,n) .It is proved that MKPS have a approxima- tion ratio better than 0 .5 for a subclass of MKP (B,S,m,n) with n≤ 1 0 0 ,m≤ 5 and maxnj=1{ wj} minmi=1{ Ci} ≤ 2 3 .展开更多
In this paper, a new class of over-relaxed proximal point algorithms for solving nonlinear operator equations with (A,η,m)-monotonicity framework in Hilbert spaces is introduced and studied. Further, by using the gen...In this paper, a new class of over-relaxed proximal point algorithms for solving nonlinear operator equations with (A,η,m)-monotonicity framework in Hilbert spaces is introduced and studied. Further, by using the generalized resolvent operator technique associated with the (A,η,m)-monotone operators, the approximation solvability of the operator equation problems and the convergence of iterative sequences generated by the algorithm are discussed. Our results improve and generalize the corresponding results in the literature.展开更多
In this paper,a new algorithm relaxation-strategy-based modification branchand-bound algorithm is developed for a type of solving the minimum cost transportationproduction problem with concave production costs.The maj...In this paper,a new algorithm relaxation-strategy-based modification branchand-bound algorithm is developed for a type of solving the minimum cost transportationproduction problem with concave production costs.The major improvement of the proposed new method is that modification algorithm reinforces the bounding operation using a Lagrangian relaxation,which is a concave minimization but obtains a tighter bound than the usual linear programming relaxation.Some computational results are included.Computation results indicate that the algorithm can solve fairly large scale problems.展开更多
基于点云的空间非合作目标位姿估计,常受到噪声影响.提出截断最小二乘估计与半定松弛(truncated least squares estimation and semidefinite relaxation,TEASER)与迭代最近点(iterative closest point,ICP)的结合算法,提升空间非合作...基于点云的空间非合作目标位姿估计,常受到噪声影响.提出截断最小二乘估计与半定松弛(truncated least squares estimation and semidefinite relaxation,TEASER)与迭代最近点(iterative closest point,ICP)的结合算法,提升空间非合作目标位姿估计精度与鲁棒性.该方法包括粗配准与精配准两个环节:在粗配准环节中,基于局部点云与模型点云的方向直方图特征(signature of histogram of orientation,SHOT)确定匹配对,利用TEASER算法求解初始位姿;在精配准环节中,可结合ICP算法优化位姿估计结果.北斗卫星仿真实验表明:在连续帧位姿估计中,噪声标准差为3倍点云分辨率时,基于TEASER的周期关键帧配准方法的平移误差小于3.33 cm,旋转误差小于2.18°;与传统ICP方法相比,平均平移误差与平均旋转误差均有所降低.这表明所提出的空间非合作目标位姿估计方法具有良好的精度和鲁棒性.展开更多
基金Projects(10872219 10672190) supported by the National Natural Science Foundation of China
文摘Based on the fact that a static problem has an equivalent wave speed of infinity and a dynamic problem has a wave speed of finite value, an effective loading algorithm associated with the explicit dynamic relaxation method was presented to produce meaningful numerical solutions for static problems. The central part of the explicit dynamic relaxation method is to turn a time-independent static problem into an artificial time-dependent dynamic problem. The related numerical testing results demonstrate that: (1) the proposed effective loading algorithm is capable of enabling an applied load in a static problem to be propagated throughout the whole system within a given loading increment, so that the time-independent solution of the static problem can be obtained; (2) the proposed effective loading algorithm can be straightforwardly applied to the particle simulation method for solving a wide range of static problems.
文摘In this paper, an absorbing Fictitious Boundary Condition (FBC) is presented to generate an iterative Domain Decomposition Method (DDM) for analyzing waveguide problems.The relaxed algorithm is introduced to improve the iterative convergence. And the matrix equations are solved using the multifrontal algorithm. The resulting CPU time is greatly reduced.Finally, a number of numerical examples are given to illustrate its accuracy and efficiency.
基金the National Natural Science Foundation of China (70631003)the Hefei University of Technology Foundation (071102F).
文摘A class of nonidentical parallel machine scheduling problems are considered in which the goal is to minimize the total weighted completion time.Models and relaxations are collected.Most of these problems are NP-hard,in the strong sense,or open problems,therefore approximation algorithms are studied.The review reveals that there exist some potential areas worthy of further research.
文摘In this paper, a new method, so called A-method, is given for the convergence analysis of the MQ-algorithm. And the finer relaxation parameter θA is obtained. The numerical results show that our new method has the outstanding effect of accelerating convergence. Moreover, the relaxation parameter θA is the optimum in a point of view.
文摘In this paper,we establish a new algorithm to the non-overlapping Schwarz domain decomposition methods with changing transmission conditions for solving one dimensional advection reaction diffusion problem.More precisely,we first describe the new algorithm and prove the convergence results under several natural assumptions on the sequences of parameters which determine the transmission conditions.Then we give a simple method to estimate the new value of parameters in each iteration.The interesting advantage of our method is that one may update the better parameters in each iteration to save the computational cost for optimizing the parameters after many steps.Finally some numerical experiments are performed to show the behavior of the convergence rate for the new method.
文摘The multisplitting algorithm for solving large systems of ordinary differential equations on parallel computers was introduced by Jeltsch and Pohl in [1]. On fixed time intervals conver gence results could be derived if the subsystems are solving exactly.Firstly,in theis paper,we deal with an extension of the waveform relaxation algorithm by us ing multisplittin AOR method based on an overlapping block decomposition. We restricted our selves to equidistant timepoints and dealed with the case that an implicit integration method was used to solve the subsystems numerically in parallel. Then we have proved convergence of multi splitting AOR waveform relaxation algorithm on a fixed window containing a finite number of timepoints.
基金Supported by the National Natural Science Foundation of China(1 9971 0 78)
文摘The multiple knapsack problem denoted by MKP (B,S,m,n) can be defined as fol- lows.A set B of n items and a set Sof m knapsacks are given such thateach item j has a profit pjand weightwj,and each knapsack i has a capacity Ci.The goal is to find a subset of items of maximum profit such that they have a feasible packing in the knapsacks.MKP(B,S,m,n) is strongly NP- Complete and no polynomial- time approximation algorithm can have an approxima- tion ratio better than0 .5 .In the last ten years,semi- definite programming has been empolyed to solve some combinatorial problems successfully.This paper firstly presents a semi- definite re- laxation algorithm (MKPS) for MKP (B,S,m,n) .It is proved that MKPS have a approxima- tion ratio better than 0 .5 for a subclass of MKP (B,S,m,n) with n≤ 1 0 0 ,m≤ 5 and maxnj=1{ wj} minmi=1{ Ci} ≤ 2 3 .
文摘In this paper, a new class of over-relaxed proximal point algorithms for solving nonlinear operator equations with (A,η,m)-monotonicity framework in Hilbert spaces is introduced and studied. Further, by using the generalized resolvent operator technique associated with the (A,η,m)-monotone operators, the approximation solvability of the operator equation problems and the convergence of iterative sequences generated by the algorithm are discussed. Our results improve and generalize the corresponding results in the literature.
基金Foundation item: Supported by the National Natural Science Foundation of China(10726016) Supported by the Hubei Province Natural Science Foundation Project(T200809 D200613002)
文摘In this paper,a new algorithm relaxation-strategy-based modification branchand-bound algorithm is developed for a type of solving the minimum cost transportationproduction problem with concave production costs.The major improvement of the proposed new method is that modification algorithm reinforces the bounding operation using a Lagrangian relaxation,which is a concave minimization but obtains a tighter bound than the usual linear programming relaxation.Some computational results are included.Computation results indicate that the algorithm can solve fairly large scale problems.
文摘基于点云的空间非合作目标位姿估计,常受到噪声影响.提出截断最小二乘估计与半定松弛(truncated least squares estimation and semidefinite relaxation,TEASER)与迭代最近点(iterative closest point,ICP)的结合算法,提升空间非合作目标位姿估计精度与鲁棒性.该方法包括粗配准与精配准两个环节:在粗配准环节中,基于局部点云与模型点云的方向直方图特征(signature of histogram of orientation,SHOT)确定匹配对,利用TEASER算法求解初始位姿;在精配准环节中,可结合ICP算法优化位姿估计结果.北斗卫星仿真实验表明:在连续帧位姿估计中,噪声标准差为3倍点云分辨率时,基于TEASER的周期关键帧配准方法的平移误差小于3.33 cm,旋转误差小于2.18°;与传统ICP方法相比,平均平移误差与平均旋转误差均有所降低.这表明所提出的空间非合作目标位姿估计方法具有良好的精度和鲁棒性.