广义C-R组的性质及两个边值问题

本文考虑广义C-R组^[1](H)的解f=u iv jw∈C^2的一些性质，提出与之相关的两个边值问题，用积分方程方法和调和函数性质证明了边值问题解的存在唯一性，并写出解的积分表达式．     

双hypergenic函数向量的带Haseman位移带共轭的边值问题

讨论实Clifford分析中双hypergenic函数向量的带Haseman位移带共轭的边值问题.首先利用积分方程和Schauder不动点定理证明了其边值问题解的存在性,再运用压缩映射原理证明了其线性边值问题解的存在唯一性,并给出解的积分表达式.     

抽象算子在偏微分方程中的应用（I）

根据解析函数和线性算子的基本性质定义了一类线性算子，建立了关于这种算子的完整理论，然后把一般形式的高阶常系数线性偏微分方程初值问题的解析解用这种算子表示出来；通过把这种算子表示成积分形式，这种算子形式的偏微分方程解就转化为积分形式的解，我们就彻底解决了把任意阶常系数线性偏微分方程初值问题的解析解求出并表示成给定函数的积分这一重要课题，而无需传统的对方程进行分类和讨论。     

Clifford分析中无界域上向量值函数的非线性边值问题

利用积分方程的方法和Arzela-Ascoli定理,讨论了Clifford分析中无界域上向量值函数的非线性边值问题解的存在性及其积分表达式.     

线性生成模糊值函数积分的Monte Carlo解法

首先利用模糊结构元方法,将模糊值函数的积分转换成等价的确定函数积分.然后,采用Monte Carlo模拟方法给出确定函数积分的数值解,进而获得原模糊值函数积分的数值解.最后,给出了具体算例.     

双解析函数的Haseman边值问题

本文利用双解析函数的Cauchy型积分和带位移的奇异积分方程方法,研究并得到了双解析函数的Haseman边值问题的一般解的表示式和可解条件以及线性无关解的个数与指标之间的关系.     

带Caratheodory函数的积分微分方程周期边值问题

本文研究了带Ｃａｒａｔｈｅｏｄｏｒｙ函数的非线性Ｖｏｌｔｅｒｒａ型积分微分方程周期边值问题，对于下解α与上解β的两种情形；α≤β或β≤α，解的存在性和建立极解的单调迭代法均被讨论。     

抽象算子在偏微分方程中的应用(Ⅰ)

根据解析函数和线性算子的基本性质定义了一类线性算子，建立了关于这种算子的完整理论，然后把一般形式的高阶常系数线性偏微分方程初值问题的解析解用这种算子表示出来；通过把这种算子表示成积分形式，这种算子形式的偏微分方程解就转化为积分形式的解，我们就彻底解决了把任意阶常系数线性偏微分方程初值问题的解析解求出并表示成给定函数的积分这一重要课题，而无需传统的对方程进行分类和讨论     

双正则函数向量的带Haseman位移带共轭值的线性及非线性边值问题

首先利用积分方程的方法和Arzela-Ascoli定理讨论了实Clifford分析中双正则函数向量的带Haseman位移带共轭值的非线性边值问题解的存在性及其积分表达式,其次利用压缩映射原理解决了其线性边值问题解的存在唯一性及其积分表达式.     

广义Q—全纯矩阵值函数的积分表示

本文研究一类平面一阶偏微分方程组的解的表示式，利用积分方程方法将方程组化为等价的第二类Ｆｒｅｄｈｏｌｍ积分方程组，建立了广义Ｑ－全纯矩阵值函数的积分表示，并且得到了广义Ｃａｕｃｈｙ积分公式。     

Long Time Asymptotic Behavior of Solution of Difference Scheme for a Semilinear Parabolic Equation

In this paper we prove that the solution of implicit difference scheme for a semilinear parabolic equation converges to the solution of difference scheme for the corresponding nonlinear stationary problem as $t\rightarrow\infty$. For the discrete solution of nonlinear parabolic problem, we get its long time asymptotic behavior which is similar to that of the continuous solution. For simplicity, we consider one-dimensional problem.     

An approach for solving nonlinear programming problems

In this paper we use measure theory to solve a wide range of the nonlinear programming problems. First, we transform a nonlinear programming problem to a classical optimal control problem with no restriction on states and controls. The new problem is modified into one consisting of the minimization of a special linear functional over a set of Radon measures; then we obtain an optimal measure corresponding to functional problem which is then approximated by a finite combination of atomic measures and the problem converted approximately to a finite-dimensional linear programming. Then by the solution of the linear programming problem we obtain the approximate optimal control and then, by the solution of the latter problem we obtain an approximate solution for the original problem. Furthermore, we obtain the path from the initial point to the admissible solution.     

The crane scheduling problem: models and solution approaches

In this paper, we study the crane scheduling problem for a vessel after the vessel is moored on a terminal and develop both exact and heuristic solution approaches for the problem. For small-sized instances, we develop a time-space network flow formulation with non-crossing constraints for the problem and apply an exact solution approach to obtain an optimal solution. For medium-sized instances, we develop a Lagrangian relaxation approach that allows us to obtain tight lower bounds and near-optimal solutions. For large-sized instances, we develop two heuristics and show that the error bounds of our heuristics are no more than 100%. Finally, we perform computational studies to show the effectiveness of our proposed solution approaches.     

To the Solution of the Hilbert Problem with Infinite Index

In this paper, we obtain a generalization of the method of regularizing multipliers for the solution of the Hilbert boundary-value problem with finite index in the theory of analytic functions to the case of an infinite power-behaved index. This method is used to obtain a general solution of the homogeneous Hilbert problem for the half-plane, a solution that depends on the existence and the number of entire functions possessing mirror symmetry with respect to the real axis and satisfying some additional constraints related to the singularity characteristic of the index. To solve of the inhomogeneous problem, we essentially use a specially constructed solution of the homogeneous problem whereby we reduce the boundary condition of the Hilbert problem to a Dirichlet problem.     

Nonuniqueness of solutions for a singular diffusion problem

In this paper, we consider a singular diffusion problem and show, by constructing a counterexample, that the weak solution to the problem is not unique. The proof consists of several steps. First, we prove that there exists a maximal weak solution to the problem. We show that the support of the continuous maximal weak solution cannot decrease in time. Then we cite an example of a nonnegative continuous function with shrinking support that also solves the problem, and therefore the problem possesses at least two weak solutions for some continuous nonnegative initial data.     

Pointwise Control of the Burgers Equation and Related Nash Equilibrium Problems: Computational Approach

This article is concerned with the numerical solution of multiobjective control problems associated with nonlinear partial differential equations and more precisely the Burgers equation. For this kind of problems, we look for the Nash equilibrium, which is the solution to a noncooperative game. To compute the solution of the problem, we use a combination of finite-difference methods for the time discretization, finite-element methods for the space discretization, and a quasi-Newton BFGS algorithm for the iterative solution of the discrete control problem. Finally, we apply the above methodology to the solution of several tests problems. To be able to compare our results with existing results in the literature, we discuss first a single-objective control problem, already investigated by other authors. Finally, we discuss the multiobjective case.     

An inner approximation method incorporating a branch and bound procedure for optimization over the weakly efficient set

In this paper, we consider an optimization problem which aims to minimize a convex function over the weakly efficient set of a multiobjective programming problem. From a computational viewpoint, we may compromise our aim by getting an approximate solution of such a problem. To find an approximate solution, we propose an inner approximation method for such a problem. Furthermore, in order to enhance the efficiency of the solution method, we propose an inner approximation algorithm incorporating a branch and bound procedure.     

Regularization of a two-dimensional strongly damped wave equation with statistical discrete data

In this paper, we consider an inverse problem for a strongly damped wave equation in two dimensional with statistical discrete data. Firstly, we give a representation for the solution and then present a discretization form of the Fourier coefficients. Secondly, we show that the solution does not depend continuously on the data by stating a concrete example, which makes the solution be not stable and thus the present problem is ill-posed in the sense of Hadamard. Next, we use the trigonometric least squares method associated with the Fourier truncation method to regularize the instable solution of the problem. Finally, the convergence rate of the error between the regularized solution and the sought solution is estimated and also investigated numerically.     

On the Cauchy problem for a generalized Boussinesq equation

In this paper, we consider the Cauchy problem for a generalized Boussinesq equation. We show that, under suitable conditions, a global solution for the initial value problem exists. In addition, we derive the sufficient conditions for the blow-up of the solution to the problem.     

An Iterative Method for Finding the Least Solution to the Tensor Complementarity Problem

In this paper, we are concerned with finding the least solution to the tensor complementarity problem. When the involved tensor is strongly monotone, we present a way to estimate the nonzero elements of the solution in a successive manner. The procedure for identifying the nonzero elements of the solution gives rise to an iterative method of solving the tensor complementarity problem. In each iteration, we obtain an iterate by solving a lower-dimensional tensor equation. After finitely many iterations, the method terminates with a solution to the problem. Moreover, the sequence generated by the method is monotonically convergent to the least solution to the problem. We then extend this idea for general case and propose a sequential mathematical programming method for finding the least solution to the problem. Since the least solution to the tensor complementarity problem is the sparsest solution to the problem, the method can be regarded as an extension of a recent result by Luo et al. (Optim Lett 11:471–482, 2017). Our limited numerical results show that the method can be used to solve the tensor complementarity problem efficiently.