利用模拟退火遗传算法实现图像阈值分割

本文提出了一种利用模拟退火算法和遗传算法相结合的图像阈值分割算法,试验结果表明该算法增强了算法的全局收敛性,加快了算法的收敛速度,提高了图像阈值分割的效率.     

多目标规划的一类基于精确罚函数的交互式方法

该文在约束集的线性化锥非空的条件下,得到了带有等式和不等式约束的多目标规划问题的精确罚函数的存在性,用原问题的二次近似在某些点上的Kuhn－Tucker乘子给出了罚因子的下界．在此基础上,利用极大熵方法的思想将罚问题转化为可微的无约束多目标规划问题并给出了求解该问题的一种交互式算法．数值结果表明：该文算法具有计算速度快、精度高、适用范围广且易于理解和使用等优点．     

求解线性Caputo分数阶微分方程的高精度数值算法

首先,研究了计算Caputo分数阶导数的数值算法,并将其应用于求解线性Caputo分数阶微分方程的初值问题,提出了求解此问题的基础数值算法.如果初值条件不足,应用基础算法将无法计算出高精度的数值解.为了解决这一问题,构造辅助函数计算缺少的初值条件,进而设计出高精度的数值算法.计算实例说明,高精度算法是有效的.     

新外推完全多重网格法北大核心

使用新外推公式和高阶插值算子,为相邻细层提供好的初值,对初值使用磨光算子磨光几次后,再调用V型多重网格法求得该层数值解,构造了基于四阶紧致差分格式的新外推完全多重网格法.数值实验表明,与对比算法相比,新算法迭代次数少、计算时间短、稳健性强.     

新外推完全多重网格法

使用新外推公式和高阶插值算子,为相邻细层提供好的初值,对初值使用磨光算子磨光几次后,再调用V型多重网格法求得该层数值解,构造了基于四阶紧致差分格式的新外推完全多重网格法.数值实验表明,与对比算法相比,新算法迭代次数少、计算时间短、稳健性强.     

基于配点GA-SQP算法的月球软着陆轨道优化设计

月球软着陆是月球探测中的一项关键技术.针对这项技术,提出基于直接配点法和GA-SQP法的月球软着陆轨道优化算法.算法通过建立月球软着陆动力学模型并进行归一化处理,利用直接配点法将月球软着陆轨道优化问题离散为非线性规划问题,应用SQP方法可求解该优化问题.同时考虑到SQP方法对初值敏感、收敛半径小及容易陷入局部极值等不足,提出了应用GA为SQP方法提供迭代初值的算法,提高了算法的稳定性.最后给出了相关的仿真结果.     

PSBH中的组合优化问题及其计算方法

本文介绍了具有部分位置信息的SBH杂交测序（Positional Sequencing by Hy-bridization,简称PSBH）实验所产生的一个重构DNA片断的组合优化问题,并讨论了该问题最优重构的计算问题.通过对PSBH提供的谱集及其位置信息的分析处理,我们获得了若干判定最优重构片断头尾的分支定界准则以及确定其非头尾位置最可能出现k-tuple的动态规划计算方法,并由此给出了该PSBH问题的一个新重构算法.该算法允许PSBH谱集含有一般杂交实验中常常可能出现探针错配所产生的正错误,并且仅仅假设PSBH的谱集、位置信息和位置长度是已知的,所以我们的算法具有更一般的适应性和实用性.此外,由于我们给出的算法能够极大地利用PSBH的谱集和位置信息所蕴含的信息确定最优重构片断头尾及其中间位置最可能出现的k-tuple,极大地减少了PSBH重构中的随意性,所以我们的算法也是有效的,模拟PSBH实验的计算结果验证了这一点.     

一种具有全局收敛性的求解二阶锥规划的非精确光滑算法

在方程组方法框架下,给出了一种求解二阶锥规划的非精确光滑算法.在适当的条件下,证明了该算法具有全局收敛性.数值试验表明该算法对求解中大规模二阶锥规划是有效的.     

广义混合非线性Schrödinger方程的拟谱方法

本文讨论了广义混合非线性Schrodinger方程的周期初值问题,构造了守恒的半离散Fourier拟谱格式,对其近似解进行了先验估计,并证明了格式的收敛性.证明了该方程存在孤立子解,并给出其孤立子解的精确表达式.研究了线性化方程的稳定性问题,即在初值有扰动的情况下,该方程只有振荡解和鞍点.最后,通过数值例子验证了格式的可信性,数值计算表明,本格式时间方向可取大步长且是长时间稳定的,我们还计算了孤立子解,并绘出了在初值有扰动的情况下,相空间的轨线图.     

广义混合非线性Schr(o)dinger方程的拟谱方法

本文讨论了广义混合非线性Schrodinger方程的周期初值问题,构造了守恒的半离散Fourier拟谱格式,对其近似解进行了先验估计,并证明了格式的收敛性.证明了该方程存在孤立子解,并给出其孤立子解的精确表达式.研究了线性化方程的稳定性问题,即在初值有扰动的情况下,该方程只有振荡解和鞍点.最后,通过数值例子验证了格式的可信性,数值计算表明,本格式时间方向可取大步长且是长时间稳定的,我们还计算了孤立子解,并绘出了在初值有扰动的情况下,相空间的轨线图.     

An Arnoldi-Extrapolation algorithm for computing PageRank

The Arnoldi-type algorithm proposed by Golub and Greif [G. Golub, C. Greif, An Arnoldi-type algorithm for computing PageRank, BIT 46 (2006) 759-771] is a restarted Krylov subspace method for computing PageRank. However, this algorithm may not be efficient when the damping factor is high and the dimension of the search subspace is small. In this paper, we first develop an extrapolation method based on Ritz values. We then consider how to periodically knit this extrapolation method together with the Arnoldi-type algorithm. The resulting algorithm is the Arnoldi-Extrapolation algorithm. The convergence of the new algorithm is analyzed. Numerical experiments demonstrate the numerical behavior of this algorithm.     

An algorithm for semi-infinite transportation problems

In this paper we consider a class of semi-infinite transportation problems. We develop an algorithm for this class of semi-infinite transportation problems. The algorithm is a primal dual method which is a generalization of the classical algorithm for finite transportation problems. The most important aspect of our paper is that we can prove the convergence result for the algorithm. Finally, we implement some examples to illustrate our algorithm.     

An algorithm for the capacitated vehicle routing problem with route balancing

In this paper, we present a multi-objective evolutionary algorithm for the capacitated vehicle routing problem with route balancing. The algorithm is based on a formerly developed multi-objective algorithm using an explicit collective memory method, namely the extended virtual loser (EVL). We adapted and improved the algorithm and the EVL method for this problem. We achieved good results with this simple technique. In case of this problem the quality of the results of the algorithm is similar to that of other evolutionary algorithms.     

含有等式约束非线性规划的全局优化算法

针对含有多个等式约束的非线性规划问题,提出一个全局优化算法.该方法基于可行集策略把改进的模拟退火方法与确定的局部算法方法相结合.对算法的收敛性进行了证明,数值结果表明算法的有效性及正确性.     

一个求大规模非负不可约稀疏矩阵的谱半径及特征向量的新算法

本文设计了一个计算非负不可约矩阵的谱半径及其特征向量的新算法,并证明了其收敛性.该算法计算晕不大,占用内存少,有相同的0元模式,从而在大规模稀疏矩阵的计算中优势明显.最后用实例验证了此算法的可行性.     

Convergence property of the Iri-Imai algorithm for some smooth convex programming problems

In this paper, the Iri-Imai algorithm for solving linear and convex quadratic programming is extended to solve some other smooth convex programming problems. The globally linear convergence rate of this extended algorithm is proved, under the condition that the objective and constraint functions satisfy a certain type of convexity, called the harmonic convexity in this paper. A characterization of this convexity condition is given. The same convexity condition was used by Mehrotra and Sun to prove the convergence of a path-following algorithm.The Iri-Imai algorithm is a natural generalization of the original Newton algorithm to constrained convex programming. Other known convergent interior-point algorithms for smooth convex programming are mainly based on the path-following approach.     

Building graph separators with the recursive rotation algorithm for the nested dissection method

A recursive rotation algorithm is built and investigated. The algorithm is a possible version of the nested dissection algorithm. The Liu algorithm builds a matrix graph separator by means of rotation of an elimination tree, which reduces the height of the latter. In this case, the nodes of the matrix graph are previously reordered by one of the well-known Cuthill-McKee algorithms, the reverse Cuthill-McKee algorithm, and the King algorithm. Then this procedure is recursively repeated. The recursive rotation algorithm is compared with the multilevel and spectral methods of graph separation for 2D finite-element grids.     

An algorithm for calculating continued fractions

A new algorithm is described in the paper for calculating continued fractions. The conditions are given under which this algorithm is faster than the hitherto fastest algorithm for handling this problem. Also the interrelation between the suggested algorithm and that for calculating a tridiagonal system of linear equations is investigated.     

多目标规划的一种混合遗传算法

本文利用遗传算法的全局搜索内能力及直接搜索算法的局部优化能力，提出了一种用于多目标规划的混合遗传算法．与Pareto遗传算法相比．本文提出的算法能提高多目标遗传算法优化搜索效率，并保证了能得到适舍决策者要求的Pareto最优解．最后，理论与实践证明其有有效性．     

A linear programming-based optimization algorithm for solving nonlinear programming problems

In this paper a linear programming-based optimization algorithm called the Sequential Cutting Plane algorithm is presented. The main features of the algorithm are described, convergence to a Karush–Kuhn–Tucker stationary point is proved and numerical experience on some well-known test sets is showed. The algorithm is based on an earlier version for convex inequality constrained problems, but here the algorithm is extended to general continuously differentiable nonlinear programming problems containing both nonlinear inequality and equality constraints. A comparison with some existing solvers shows that the algorithm is competitive with these solvers. Thus, this new method based on solving linear programming subproblems is a good alternative method for solving nonlinear programming problems efficiently. The algorithm has been used as a subsolver in a mixed integer nonlinear programming algorithm where the linear problems provide lower bounds on the optimal solutions of the nonlinear programming subproblems in the branch and bound tree for convex, inequality constrained problems.