连续型多通道最速路问题研究

研究网络N=(V,A,c,l)上任意两节点间的多通道最速路(MQP)问题.提出MQP 的数学模型,并讨论了其最优解的充要条件.最后得出解的计算公式和一种适于动态网络环 境的MQP算法.     

实时离散事件动态系统的状态行为与最速控制

基于Ｄ－自动机模型，通过广义状态谓词空间与半范数的概念，深入研究了实时ＤＥＤＳ的状态行为及最速控制问题，最后讨论了此类控制问题解的存在性。     

一个面向对象的多通道-多媒体用户界面核心系统的实现

提出的基于事件－目标结构的多通道－多媒体用户界面的结构模型能解决复杂应用对语义反馈能力的要求和对话独立原则之间的矛盾。用Ｃ＋＋语言实现一个面向对象的多通道－多媒体用户界面软件结构,形成一个平台独立的多通道－多媒体用户界面核心系统。     

卫星多通道遥测选通电路抗串扰设计

卫星多通道遥测选通电路抗串扰设计方案优化了级联方式多路开关电路,可以解决第一级多路开关同时选通多路遥测造成的线间串扰问题。卫星多通道遥测选通电路抗串扰设计方案同时优化了模拟量遥测运放输出接口电路,可以通过匹配电阻减小模拟量遥测传输线间串扰电压。     

多通道融合算法和软件平台的实现

针对多通道用户界面的核心问题－多通道融合,分析了多通道输入流的特点,针对多通道任务的特点,把多通道输入区分为动作输入和参数输入。提出了任务注册的概念,并由此实现了以多通道任务管理器为核心的融合平台,最后提出一种结合多通道任务管理器的通用融合算法。     

最速网络消息传播问题及其模拟进化算法*

首次提出了最速网络消息传播问题族,建立了其基本问题的严格数学模型,并给出了相应的模拟进化求解算法.通过分析最速网络消息传播基本问题的特征,包括决策变量的特点、决策的网络时空影响特殊模式以及网络消息分布状态特点,构建了问题的最优化模型,并分析了该模型的可扩展性.利用决策变量的二元取值特点和单一轮次信息交互模式的相对独立性...     

基于单片DSP的16通道全双工G．723．1编解码系统

介绍了TMS320C6201数字信号处理器和ITU－T G．723。1与音压缩标准。分析了以C6201实现多通道声码器的设计要点,设计了一个用于IP电话系统的多通道实时语音编解码子系统。该系统实现ITU G6．723．1包括附录A在内的全部功能,通过了ITU的所有测试矢量。在一片主频为200MHz的C6201上,可以全双工实时处理16路话音。     

关于通用多通道整合模板的研究

针对多通道用户界面的核心问题——多通道整合，旨在对来自不同通道的信息进行合一化处理，最终向计算机正确传达用户意图。围绕多通道整合问题，通过分析多通道输入信息流的特点，提出了一个通用多通道整合功能模板的思想。通过对多通道系统语义的通用描述模型的研究，面向开发人员提供可重用通用多通道整合模板的支持。并给出了一个具体的实现方法。     

关于通用多通道整合模板的研究

针对多通道用户界面的核心问题——多通道整合,旨在对来自不同通道的信息进行合一化处理,最终向计算机正确传达用户意图。围绕多通道整合问题,通过分析多通道输入信息流的特点,提出了一个通用多通道整合功能模板的思想。通过对多通道系统语义的通用描述模型的研究,面向开发人员提供可重用通用多通道整合模板的支持。并给出了一个具体的实现方法。     

一种基于多条件约束的QoS路由选择优化算法

基于多条件约束的QoS路由选择优化是当前通信网络中的一个重要问题。研究了一类通信网络的源－目的QoS路由选择问题。通过分析,为了不失一般性,选择时延和丢失率为QoS参数,建立了一个带有丢失率约束－条件的最小时延的QoS路由选择的非线性整数规划模型,并根据模型特点,给出了用线性整数规划迭代求精确解的算法。该算法可以方便地推广到多个QoS参数的情况。最后,实例表明所提出的模型和算法是有效的。     

Markov decision process in the problem of dynamic pricing policy

Markov decision processes (MDP) are widely used in problems whose solutions may be represented by a certain series of actions. A lot of papers demonstrate successful MDP use in model problems, robotic control problems, planning problems, etc. In addition, economic problems have the property of multistep motion towards a goal as well. This paper is dedicated to MDP application to the problem of pricing policy management. The problem of dynamic pricing is stated in terms of MDP. Additional attention is paid to the method of constructing an MDP model based on data mining. Based on the data on sales of an actual industrial plant, construction of an MDP model that includes the searching for and generalization of regularities is demonstrated.     

Finding optimal strategies in a multi-period multi-leader–follower Stackelberg game using an evolutionary algorithm

Stackelberg games are a classic example of bilevel optimization problems, which are often encountered in game theory and economics. These are complex problems with a hierarchical structure, where one optimization task is nested within the other. Despite a number of studies on handling bilevel optimization problems, these problems still remain a challenging territory, and existing methodologies are able to handle only simple problems with few variables under assumptions of continuity and differentiability. In this paper, we consider a special case of a multi-period multi-leader–follower Stackelberg competition model with non-linear cost and demand functions and discrete production variables. The model has potential applications, for instance in aircraft manufacturing industry, which is an oligopoly where a few giant firms enjoy a tremendous commitment power over the other smaller players. We solve cases with different number of leaders and followers, and show how the entrance or exit of a player affects the profits of the other players. In the presence of various model complexities, we use a computationally intensive nested evolutionary strategy to find an optimal solution for the model. The strategy is evaluated on a test-suite of bilevel problems, and it has been shown that the method is successful in handling difficult bilevel problems.     

基于Petri网的作战计划制定协作模型研究

协作模型是设计多平台作战计划制定系统的关键技术之一,文章提出了协作过程冲突的几种典型模式,利用Petri网的过程仿真方法,设计并验证了解决冲突的协作模型,认为协作模型不能解决所有冲突问题,在协作模型与业务模型中分别处理协作制定的冲突问题是系统设计的有效方法。     

Solving vehicle routing problems by maximum neuron model

In this paper, we propose a new clustering method for the first phase of a two-phase method of the vehicle routing problems (VRPs) and the traveling salesman problems (TSPs). In the first phase, the customers are grouped as several delivery areas for vehicle by using maximum neuron model. In the second phase, the TSPs for each areas are solved by using elastic net model proposed by Andrew et al. Conventional maximum neuron model proposed by Takefuji et al. is not suitable for these continuous problems. But by including a self-organization rule to this model, the solution quality is improved. Our simulation results show that maximum neuron model can achieve to obtain better solutions than other methods for some kinds of problems in VRPs and TSPs.     

基于多Agent的组合模型链分布式求解算法及实现

在决策支持系统中,组合模型往往是解决复杂决策问题的有效途径,但无论采用何种模型组合技术,随着模型库模型的增多,模型组合过程中生成的模型链数量都会快速增加,这样势必造成求解速度上的瓶颈。针对这种情况,文章提出了一种基于多Agent的组合模型分布式求解模型,充分利用分布式技术快速对组合模型实现并行求解,从而提高模型组合求解的效率,保证决策的实时性。     

关于OCSP应用模式的注记

文献《在线证书状态协议的改进及应用》提出了一个基于OCSP(Online Certificate Status Protocol,在线证书状态协议)查询的数字签名验证应用方案,这个方案的安全性与可行性是值得商榷的。该文给出了一种攻击方法,并分析了其中的几个问题及问题产生的根源;最后给出了一种解决方案。     

Information flow control in multithread applications based on access control lists

Information flow control models prevent information leakage during the execution of an application. We developed a model OORBAC to control information flows in object-oriented systems. Soon after the development of OORBAC, we identified that the model cannot solve the problems induced by multithreaded applications. We thus adapted the concepts of OORBAC to develop a new information flow control model. It offers the features of OORBAC and solves the problems induced by multithread object-oriented applications. The new model is named MtACL (information flow control model for multithreaded object-oriented applications based on access control lists). The multithreaded problems solved by MtACL include the shared memory problem, the non-interference problem, and the combination leakage problem. This paper presents MtACL and proves that the model solves the multithreaded problems.     

A neural network model for monotone linear asymmetric variationalinequalities

A linear variational inequality is a uniform approach for some important problems in optimization and equilibrium problems. We give a neural network model for solving asymmetric linear variational inequalities. The model is based on a simple projection and contraction method. Computer simulation is performed for linear programming (LP) and linear complementarity problems (LCP). The test results for the LP problem demonstrate that our model converges significantly faster than the three existing neural network models examined in a comparative study paper.     

Mixed model U-line balancing type-1 problem: A new approach

Avoiding work overload (imbalance) in mixed model U-line production systems entails an investigation into both balancing and sequencing problems at the same time and that is why some authors have considered both planning problems simultaneously. However because of the existing differences between planning horizons of balancing and sequencing problems (the former is a long to mid-term planning problem whereas the latter has a short term planning horizon) this simultaneous approach is only practical under very special conditions. It is also known that installation of an assembly line usually needs considerable capital investments and consequently it is necessary to design and balance such a system so that it works as efficiently as possible. To do so, in this paper, we develop a new approach to balance a mixed model U-shaped production system independent of what product sequences may be. This new approach is based on minimization of crossover workstations. Due to utilization of crossover workstations, balancing mixed model assembly lines in U-shaped line layouts is more complicated than that of straight lines. Some kind of issues including the ‘model mixes’ appearing in such workstations and the time taken for an operator to move from one side of the line to another increase the complexity of mixed model U-line balancing problems (MMULBP). Therefore it seems reasonable to develop a model in which minimizing the number of crossover workstations and maximizing the line efficiency are considered at the same time. Such a model is presented in this paper. In the proposed model, minimizing the variation of workload is also considered and taking into account operator's travel times, an extra time is assigned to workload of crossover workstations. Furthermore a genetic algorithm (GA) is proposed and a number of well-known test problems are solved by the GA and the related results are illustrated. Finally, the conclusion is presented.     

一种基于移动Agent的分布式并行计算模型

针对传统的分布式并行计算方案所存在的缺点,提出了一种基于移动Agent技术的分布式并行计算模型。在简单介绍移动Agent技术后,给出了基于移动Agent的分布式并行计算模型,并详细叙述了该模型的具体工作过程和实现方案。模型设计完成后,用此模型来解决计算量很大的数值计算问题。首先利用数学工具分析设计出该问题的适合于分布式并行计算的方案,然后依照模型实现实验程序。实验测试表明根据该模型实现的分布式并行计算程序具有较高的加速比和并行效率,并有效地提高了分布式并行计算的稳定性、灵活性、可扩展性和移动性。