二阶常系数非齐次线性微分方程的通解公式

根据二阶常系数齐次线性微分方程的特征根,利用降阶法,可给出求解一般二阶常系数非齐次线性微分方程的通解公式.     

一类二阶常系数非齐次线性微分方程及边值问题的解法

利用非齐次方程通解方法和Green函数法给出了非齐次项为点源函数的二阶常系数线性常微分方程及边值问题的求解方法和公式.然后以渗流力学一类具体问题为例进行了论证.结果表明这两种方法在本质上是一致的,所得到的结果是相互吻合的.该点源解可用于分析相关边值问题,并可用来求解具有一般非齐次项的微分方程及相关定解问题.     

边界条件齐次化辅助函数的统一形式

用分离变量法求解数理方程混合问题时,要求其第一、二、三类边界条件必须是齐次的.若为非齐次的,必须寻求恰当的辅助函数w(x,t),进行变换将其化为齐次的.本文从稳定条件下的线性非齐次边界条件出发,给出了w(x,t)的统一形式,进而将其推广到非稳定条件下的非齐次边界条件,得到w(x,t)的一般的结果.     

用升阶法求常系数线性非齐次差分方程的特解

利用升阶法可求解常系数线性非齐次差分方程的特解．     

累次齐次平衡法及其应用

在求非线性偏微分方程精确解的过程中两次使用了齐次平衡法(称为累次齐次平衡法),解决了齐次平衡法求解少的不足,从而改进了齐次平衡法.以高阶(2+1)维Kadomtsev-Petviashvili方程和变异的Boussinesq方程为应用实例,说明使用累次齐次平衡法可以求得大量的精确解,其中许多解是新解或覆盖了其他方法所得的解.方法可应用于大量的非线性物理模型.     

线性常系数非齐次微分方程特解的卷积表示

利用卷积表示线性常系数非齐次微分方程的特解，可简化方程求解过程，方程的自由项也可被推广到任意可积函数。     

线性定常系统非齐次两点边值问题的扩展精细积分方法

提出了一种求解非齐次线性两点边值问题的高精度和高稳定的扩展精细积分方法（EPIM）.首先引入了区段量（即区段矩阵和区段向量）来离散非齐次线性微分方程,建立了非齐次两点边值问题基于区段量的求解框架.在该框架下,不同区段的区段量可以并行计算,整体代数方程组的集成不依赖于边界条件.然后引入区段响应矩阵来处理两点边值问题的非齐次项,导出了多项式函数、指数函数、正/余弦函数及其组合函数形式的非齐次项对应的区段响应矩阵的加法定理,结合增量存储技术提出了EPIM.对具有上述函数形式的非齐次项,该方法可以得到计算机上的精确解,一般形式的非齐次项则利用上述函数近似求解.最后通过两个具有刚性特征的数值算例验证了该方法的高精度和高稳定性.     

用积分因子的思想和分部积分法求解常系数非齐次线性方程

用积分因子的思想和分部积分法求解了常系数非齐次线性方程,给出了一般的常系数非齐次线性方程的求解方法.     

一类特殊非齐次树上非齐次马尔可夫链的强律

极限定理一直是国际概率论界研究的中心课题之一.本文通过构造适当的辅助非负鞅而给出了一类特殊非齐次树上可列非齐次马尔可夫链场的若干强律.     

压电热弹性体的变分原理及正则方程和齐次方程

结合对偶变量理论,为压电热弹性体混合层合板问题推导了齐次的控制方程和Hamilton等参元列式．首先根据广义的Hamilton变分原理推导了压电热弹性体非齐次的Hamilton正则方程．然后进一步考虑了热平衡方程与导热方程中变量的对偶关系,通过增加正则方程的维数,成功地将非齐次的正则方程转化为能独立求解压电热弹性体耦合问题的齐次控制方程．为了推导四节点Hamilton等参元列式的方便,可将温度梯度关系类比成本构关系并构建新的变分原理．齐次方程大大简化了人们在分析压电热弹性体耦合问题时,通常要求解非齐次方程和关于平衡方程和导热方程的二阶微分方程的繁琐方法,同时也减少了数值计算工作量．     

一些类型的数学规划问题的全局最优解

本文对严格单调函数给出了几个凸化和凹化的方法，利用这些方法可将一个严格单调的规划问题转化为一个等价的标准D．C．规划或凹极小问题．本文还对只有一个严格单调的约束的非单调规划问题给出了目标函数的一个凸化和凹化方法，利用这些方法可将只有一个严格单调约束的非单调规划问题转化为一个等价的凹极小问题．再利用已有的关于D．C．规划和凹极小的算法，可以求得原问题的全局最优解．     

Polynomial Algorithms for a Class of Discrete Minmax Linear Programming Problems

We consider the problem of obtaining integer solutions to a minmax linear programming problem. Although this general problem is NP-complete, it is shown that a restricted version of this problem can be solved in polynomial time. For this restricted class of problems two polynomial time algorithms are suggested, one of which is strongly polynomial whenever its continuous analogue and an associated linear programming problem can be solved by a strongly polynomial algorithm. Our algorithms can also be used to obtain integer solutions for the minmax transportation problem with an inequality budget constraint. The equality constrained version of this problem is shown to be NP-complete. We also provide some new insights into the solution procedures for the continuous minmax linear programming problem.     

A linear program for the two-hub location problem

This paper considers the discrete two-hub location problem. We need to choose two hubs from a set of nodes. The remaining nodes are to be connected to one of the two hubs which act as switching points for internodal flows. A configuration which minimizes the total flow cost needs to be found. We show that the problem can be solved in polynomial time when the hub locations are fixed. Since there are at most ways to choose the hub locations, the two-hub location problem can be solved in polynomial time. We transform the quadratic 0–1 integer program of the single allocation problem in the fixed two-hub system into a linear program and show that all extreme points of the polytope defined by the LP are integral. Also, the problem can be transformed into a minimum cut problem which can be solved efficiently by any polynomial time algorithm.     

求解凸不等式问题的熵光滑化方法

The maximal entropy principle is applied to solve convex inequality problems. An inequality problem can be transformed into a minmax problem.Then it can be transformed into an unconstrained parameterized min problem,using the entropic function to smooth the minmax problem. The solution of the inequality problem can be obtained, by solving the parameterized min problems and adjusting the parameter to zero, under a certain principle. However, it is sufficient to solve a parameterized inequality problem each time, from the propositions of the aggregate function. In the article, some propositions of the aggregate function are discussed, the algorithm and its convergence are obtained.     

A Fourier-Coefficient Based Solution of an Optimal Control Problem in Quantum Chemistry

We consider an optimal control problem for the time-dependent Schrödinger equation modeling molecular dynamics. The dynamics can be steered by interactions with a tuned laser field. The problem of designing an optimal field can be posed as an optimal control problem. We reformulate the optimization problem by using a Fourier transform of the electric field, and narrow the frequency band. The resulting problem is less memory intense, and can be solved with a superlinearly convergent quasi-Newton method. We show computational results for a Raman-transition example and give numerical evidence that our method can outperform the standard monotonically convergent algorithm.     

三种新变形的全一问题

该文研究三种新变形的全一问题及最小全一问题. 原始的全一问题可被形象的称为顶点点亮顶点问题, 而这三类新问题则分别被称为顶点点亮边问题,边点亮顶点问题,边点亮边问题. 顶点点亮顶点问题已经得到了广泛的研究. 比如,解的存在性问题和求解的有效算法已经被解决,一般图上的最小顶点点亮顶点问题已经被证明是NP- 完备的,树、单圈图和双圈图上的最小顶点点亮顶点问题的线性时间最优算法也已被给出等. 该文对于顶点点亮边问题,证明一个图有解当且仅当它是二部图,因此只可能有两组解和最优解. 对于边点亮顶点问题,证明一个图有解当且仅当它包含偶数个顶点,并通过将其最优问题多项式变换成最小权的完美匹配问题,得出一般图上的最小边点亮顶点问题可在多项式时间内求解. 边点亮边问题可归约成线图上的顶点点亮顶点问题.     

On the block upper-triangularity of undiscounted multi-chain markov decision problems

We show that the LP formulation for an undiscounted multi-chain Markov decision problem can be put in a block upper-triangular form by a polynomial time procedure. Each minimal block (after an appropriate dynamic revision) gives rise to a single-chain Markov decision problem which can be treated independently. An optimal solution to each single-chain problem can be connected by auxiliary dual programs to obtain an optimal solution to a multi-chain problem.     

Round robin tournaments and three index assignments

Scheduling a sports league can be seen as a difficult combinatorial optimization problem. We study some variants of round robin tournaments and analyze the relationship with the planar three-index assignment problem. The complexity of scheduling a minimum cost round robin tournament is established by a reduction from the planar three-index assignment problem. Furthermore, we introduce integer programming models. We pick up a popular idea and decompose the overall problem in order to obtain two subproblems which can be solved sequentially. We show that the latter subproblem can be casted as a planar three-index assignment problem. This makes existing solution techniques for the planar three-index assignment problem amenable to sports league scheduling.     

Convexification, Concavification and Monotonization in Global Optimization

We show in this paper that via certain convexification, concavification and monotonization schemes a nonconvex optimization problem over a simplex can be always converted into an equivalent better-structured nonconvex optimization problem, e.g., a concave optimization problem or a D.C. programming problem, thus facilitating the search of a global optimum by using the existing methods in concave minimization and D.C. programming. We first prove that a monotone optimization problem (with a monotone objective function and monotone constraints) can be transformed into a concave minimization problem over a convex set or a D.C. programming problem via pth power transformation. We then prove that a class of nonconvex minimization problems can be always reduced to a monotone optimization problem, thus a concave minimization problem or a D.C. programming problem.     

An optimization approach for communal home meal delivery service: A case study

This paper is the first to discuss the communal home meal delivery problem. The problem can be modelled as a multiple travelling salesman problem with time windows, that is closely related to the well-studied vehicle routing problem with time windows. Experimental results are reported for a real-life case study from Central Finland over several alternative scenarios using the SPIDER commercial solver. The comparison with current practice reveals that a significant savings potential can be obtained using off-the-shelf optimization tools. As such, the potential for supporting real-life communal routing problems can be considered to be important for VRP practitioners.