粘性解框架下的完全耦合正倒向随机系统最优控制问题的验证定理

研究了完全耦合正倒向随机控制系统的最优控制问题.得到了粘性解框架下的,控制变量同时出现在正倒向随机系统的漂移项和扩散项中的最优控制问题的验证定理.还讨论了验证定理在构造随机最优反馈控制中的应用.     

基于类Lyapunov函数的非线性切换系统的Reach-While-Stay性质验证

考虑了一类连续时间切换系统在任意切换信号下的Reach-While-Stay性质验证问题,提出了基于类Lyapunov函数的验证方法.首先,利用不变集构建了新的RWS性质判定准则,将RWS性质验证问题转化为关于类Lyapunov函数的非线性约束求解问题,然后运用平方和松弛进行编码,进而将其转化为双线性矩阵不等式问题并应用迭代的半定规划进行求解.最后,通过实例表明了该方法的可行性和有效性.     

关于总加权提前损失的单机排序问题

研究了最小化总加权提前损失单机排序问题,其中提前损失是工件在工期之前完成的各部分的持续加工时间.首先,文章分析了总加权提前损失问题在中断情况下的复杂性,提出了中断排序算法,用算例进行了验证;接着通过设计拟多项式动态规划算法,说明该问题在非中断情况下是一般意义下NP难的,并进行了数据实验,验证了该算法的有效性.     

一类非线性外问题的数值解法

本文利用FEM-BEM方法研究平面上一类非线性外问题数值方法, 给出了基于非线性人工边界条件的耦合问题收敛性结果和误差估计.数值算例验证了我们的理论分析结果. 最后, 我们提出求解其耦合问题的一种区域分解算法.     

Burgers-Huxley方程的同伦分析解

针对Burgers-Huxley方程定解问题,构造了一种零阶同伦方程,采用同伦方法得到Burgers-Huxley方程定解问题的近似解析解.最后,进行了实例验证和结果分析.     

求解热源识别问题的修正吉洪诺夫正则化方法

该文研究了一个热源识别问题,通过引入修正吉洪诺夫方法来处理问题的不适定性,在一种先验和一种后验参数选取准则下,分别获得了问题的误差估计.数值例子进一步验证了方法的有效性和稳定性.     

随机椭圆最优控制问题的随机配置方法

本文讨论求解随机系数泊松方程约束最优控制问题的有效数值方法.通过应用有限元方法和随机配置法,将原最优控制问题离散转化为最优化问题,再利用交替方向乘子法求解最优化问题.之后,对所提出的算法进行了收敛性分析,并通过数值实验验证了算法的有效性.     

一类随机系统平稳分布的存在性与唯一性

本文研究了一类随机系统平稳分布存在唯一性问题.利用耦合方法,给出了一个充分条件,验证该条件只需计算一些耦合,具较强的可操作性.     

基于光的波粒二象性猜想的数学建模与仿真

光具有波粒二象性,诸多学者都对此提出了不同猜想,用以合理解释光的直线传播、衍射和干涉等问题.对三种基于光的波粒二象性的猜想进行了数学建模与仿真验证.以Matlab为工具对光的衍射等现象的进行了数学仿真,并与《光学原理》中的相关结果作了对比,最终验证了猜想的正确性.     

Plate Contact问题的混合有限元逼近

论文考虑了Plate Contact问题的混合有限元逼近,其变分问题为第二类四阶椭圆变分不等问题.首先,根据正则化方法,得到原问题的正则化问题.再根据网格依赖范数技巧,考虑了正则化问题的Ciarlet-Raviart混合有限元逼近,并证明了真解与逼近解之间的误差估计.最后通过数值算例验证了理论分析的结果.     

Heuristic Solution Methods for the Multilevel Generalized Assignment Problem

The multilevel generalized assignment problem is a problem of assigning agents to tasks where the agents can perform tasks at more than one efficiency level. A profit is associated with each assignment and the objective of the problem is profit maximization. Two heuristic solution methods are presented for the problem. The heuristics are developed from solution methods for the generalized assignment problem. One method uses a regret minimization approach whilst the other method uses a repair approach on a relaxation of the problem. The heuristics are able to solve moderately large instances of the problem rapidly and effectively. Procedures for deriving an upper bound on the solution of the problem are also described. On larger and harder instances of the problem one heuristic is particularly effective.     

Complexities and algorithms for synchronized scheduling of parallel machine assembly and air transportation in consumer electronics supply chain

In this paper, we study the problem of synchronized scheduling of assembly and air transportation to achieve accurate delivery with minimized cost in consumer electronics supply chain. This problem was motivated by a major PC manufacturer in consumer electronics industry. The overall problem is decomposed into two sub-problems, which consist of an air transportation allocation problem and an assembly scheduling problem. The air transportation allocation problem is formulated as an integer linear programming problem with the objective of minimizing transportation cost and delivery earliness tardiness penalties. The assembly scheduling problem seeks to determine a schedule ensuring that the orders are completed on time and catch the flights such that the waiting penalties between assembly and transportation is minimized. The problem is formulated as a parallel machine scheduling problem with earliness penalties. The computational complexities of the two sub-problems are investigated. The air transportation allocation problem with split delivery is shown to be solvable. The parallel machine assembly scheduling problem is shown to be NP-complete. Simulated annealing based heuristic algorithms are presented to solve the parallel machine problem.     

Continuous quadratic programming formulations of optimization problems on graphs

Four NP-hard optimization problems on graphs are studied: The vertex separator problem, the edge separator problem, the maximum clique problem, and the maximum independent set problem. We show that the vertex separator problem is equivalent to a continuous bilinear quadratic program. This continuous formulation is compared to known continuous quadratic programming formulations for the edge separator problem, the maximum clique problem, and the maximum independent set problem. All of these formulations, when expressed as maximization problems, are shown to follow from the convexity properties of the objective function along the edges of the feasible set. An algorithm is given which exploits the continuous formulation of the vertex separator problem to quickly compute approximate separators. Computational results are given.     

Uncertain solid transportation problems

The solid transportation problem arises when bounds are given on three item properties. Usually, these properties are source, destination and type of product or mode of transport, and often are given in a uncertain way. This paper deals with two of the ways in which uncertainty can appear in the problem: Interval solid transportation problem and fuzzy solid transportation problem. The first arises when data problem are expressed as intervals instead of point values, and the second when the nature of the information is vague. Both models are treated in the case in which the uncertainty affects only the constraint set. For interval case, an auxiliary problem is obtained in order to find a solution. This auxiliary problem is a standard solid transportation problem which can be solved with the efficient methods existing. For fuzzy case, a parametric approach which makes it possible to find a fuzzy solution to the former problem is used.     

Fuzzy weighted equilibrium multi-job assignment problem and genetic algorithm

In this paper, the equilibrium optimization problem is proposed and the assignment problem is extended to the equilibrium multi-job assignment problem, equilibrium multi-job quadratic assignment problem and the minimum cost and equilibrium multi-job assignment problem. Furthermore, the mathematical models of the equilibrium multi-job assignment problem and the equilibrium multi-job quadratic assignment problem with fuzzy parameters are formulated. Finally, a genetic algorithm is designed for solving the proposed programming models and some numerical examples are given to verify the efficiency of the designed algorithm.     

Scheduling a single machine to minimize earliness penalties subject to the SLK due-date determination method

This paper considers a single machine scheduling problem. There are n jobs to be processed on a single machine. The problem is to minimize total earliness penalties subject to no tardy jobs. The problem is NP-complete if the due-dates are arbitrary. We study the problem when the due-dates are determined by the equal slack (SLK) method. Two special cases of the problem are solved in polynomial time. The first one is the problem with equally weighted monotonous penalty objective function. The second one is the problem with weighted linear penalty objective function.     

Production planning with discounting and stochastic demands

A general continuous review production planning problem with stochastic demand is considered. Conditions under which the stochastic problem may be correctly solved using an equivalent deterministic problem are developed. This deterministic problem is known to have the same solution as the stochastic problem. Moreover, conditions are established under which the deterministic equivalent problem differs from a commonly used deterministic approximation to the problem only in the interest rate used in discounting. Thus, solving the stochastic problem is no more difficult than solving a commonly used approximation of the problem.     

Solution of Finite-Dimensional Variational Inequalities Using Smooth Optimization with Simple Bounds

The variational inequality problem is reduced to an optimization problem with a differentiable objective function and simple bounds. Theoretical results are proved, relating stationary points of the minimization problem to solutions of the variational inequality problem. Perturbations of the original problem are studied and an algorithm that uses the smooth minimization approach for solving monotone problems is defined.     

单体型装配问题及其算法

单核苷酸多态性(SNP)单体型装配问题就是从给定的来自某人染色体的SNP片段中去除错误,重构出尽可能与原来片段一致的单体型.这个问题有几个不同的模型最少片段去除(MFR)问题,最少SNP去除(MSR)问题以及最少错误纠正(MEC)问题.前两个问题的复杂性与算法已有一些学者研究过.第三个问题已被证明是NP完全问题,但这个问题的实际算法还没有.该文对MEC问题给出了一个分支定界算法,这个算法能得到问题的全局最优解.通过这个算法对实际数据的计算说明了MEC模型的合理性,即在一定条件下,通过修正最少的错误重构出的单体型确实是真实的单体型.由于分支定界算法对这样一个NP完全问题不能在可接受的时间内解规模较大的问题,文中又给出了求解MEC问题的两个基于动态聚类的算法,以便对规模较大的问题在可接受的时间内得到近似最优解.数值实际表明这两个算法很快,很有效.这两个算法总能得到与分支定界找到的全局最优解很接近的近似最优解.鉴于MEC问题是NP完全的,这两个算法是有效的、实际的算法.     

线性比式和规划问题的输出空间分支定界算法

本文旨在针对线性比式和规划这一NP-Hard非线性规划问题提出新的全局优化算法.首先,通过引入p个辅助变量把原问题等价的转化为一个非线性规划问题,这个非线性规划问题的目标函数是乘积和的形式并给原问题增加了p个新的非线性约束,再通过构造凸凹包络的技巧对等价问题的目标函数和约束条件进行相应的线性放缩,构成等价问题的一个下界线性松弛规划问题,从而提出了一个求解原问题的分支定界算法,并证明了算法的收敛性.最后,通过数值结果比较表明所提出的算法是可行有效的.