QoS路由近似算法的研究

QoS需求可分为基于路径的与基于链路的两种。称一个具有足够资源来满足应用QoS需求的路径为可行路径。另外,优化准则可以进一步缩小在可行路径间的选择范围。QoS路由的目标是寻找最优的可行路径。基于QoS的路由是当前的一个研究热点,其目标是在确定满足多个约束条件(QoS需求)的路径的同时实现网络资源的高利用率。基于QoS的路由对资源预置的服务(如IntServ,ATM)与非资源预置的服务(如DiffServ)都是需要的。如,ATM PNNI(Private Network Node Interface)协议基     

An exact approach for scheduling jobs with regular step cost functions on a single machine

This paper studies a single-machine scheduling problem whose objective is to minimize a regular step total cost function. Lower and upper bounds, obtained from linear and Lagrangian relaxations of different Integer Linear Programming formulations, are compared. A dedicated exact approach is presented, based on a Lagrangian relaxation. It consists of finding a Constrained Shortest Path in a specific graph designed to embed a dominance property. Filtering rules are developed for this approach in order to reduce the size of the graph, and the problem is solved by successively removing infeasible paths from the graph. Numerical experiments are conducted to evaluate the lower and upper bounds. Moreover, the exact approach is compared with a standard solver and a naive branch-and-bound algorithm.     

Optimization-Oriented Global Constraints

In this paper, we propose a way of exploiting Operations Research techniques within global constraints for cost-based domain filtering. In Constraint Programming, constraint propagation is aimed at removing from variable domains combinations of values which are proven infeasible. Pruning derives from feasibility reasoning. When coping with optimization problems, pruning can be performed also on the basis of costs, i.e., optimality reasoning. Cost-based filtering removes combination of values which are proven sub-optimal. For this purpose, we encapsulate in global constraints optimization components representing suitable relaxations of the constraint itself. These components embed efficient Operations Research algorithms computing the optimal solution of the relaxed problem and a gradient function representing the estimated cost of each variable-value assignment. We exploit these pieces of information for pruning and for guiding the search. We have applied these techniques to a couple of ILOG Solver global constraints (a constraint of difference and a path constraint) and tested the approach on a variety of combinatorial optimization problems such as Timetabling, Travelling Salesman Problems and Scheduling Problems with sequence dependent setup times. Comparisons with pure Constraint Programming approaches and related literature clearly show the benefits of the proposed approach.     

求解最短路径问题的Lotka-Volterra回复式神经网络模型

有向图的最短路径(SP)问题是一个优化问题。通过构造有向图的最短路径问题的能量函数,提出了一种Lotka-Volterra (LV)回复式神经网络(RNN)模型,用于求解有向图的最短路径。当LV神经网络迭代收敛到稳定吸引子时,对应的能量函数也达到其能量最小点。因此,通过稳定吸引子可以获取最短路径。实验结果表明,利用LV神经网络模型可以有效地求解有向图中任意两个顶点之间的最短路径。     

Traffic recovery time constrained shared sub-path protection algorithm in survivable WDM networks

With the development of real-time applications, the traffic recovery time, which is defined as the duration between the failure occurrence on the working path and the interruptive traffic has been successfully switched to the backup path, has become the basic Quality-of-Service (QoS) requirement in survivable WDM networks. In this paper, we address the problem of shared sub-path protection with considering the constraint of traffic recovery time and propose a new heuristic algorithm called Traffic recovery time Constrained Shared Sub-Path Protection (TC_SSPP) to compute the working path and the Shared-Risk-Link-Group (SRLG)-disjoint backup sub-paths. The main target of our work is to improve the resource utilization ratio and reduce the blocking probability for dynamic network environment. By properly setting the delay parameter for each link and running the Delay Constrained Shortest Path Algorithm (DCSPA) to compute the backup sub-paths, TC_SSPP can effectively guarantee the traffic recovery time. Simulation results show that the proposed TC_SSPP can outperform the traditional algorithms.     

低代价最短路径树的快速算法

低代价最短路径树是一种广泛使用的多播树.它能够在保证传送时延最小的同时尽量降低带宽消耗.在DDSP(destination-driven shortest path)算法的基础上,通过改进节点的搜索过程,提出了快速低代价最短路径树算法FLSPT(fast loW-coSt shortest path tree).该算法构造的最短路径树与DDSP算法构造的树具有相同的性能,但其时间复杂度低于DDSP算法.随机网络模型的仿真结果表明,FLSPT算法效率更高.     

基于优化链路权值的域内路由保护方案

目前,互联网部署的域内链路状态路由协议,如开放最短路径优先(Open Shortest Path First,OSPF)和中间系统到中间系统(Intermediate System-to-Intermediate System,IS-IS),采用被动恢复方案应对网络故障。随着网络的发展,大量的实时应用部署在互联网上,OSPF的收敛时间无法满足这些实时应用对收敛时间的需求。因此,学术界和工业界提出采用路由保护方案来应对网路中出现的故障。然而,已有的路由保护方案存在两个方面的问题:1)默认路径和备份路径的交叉度较高,如LFA；2)为了计算两条交叉度低的路径,对默认路径加以限制,即默认路径不采用最短路径,如Color Tree。为了解决上述两个问题,首先将上述问题归结为整数规划模型,接着利用启发式方法计算近似最优解,最后在实际网络和模拟网络中对所提算法进行了大量实验。实验结果表明,所提算法可以降低默认路径和备份路径的交叉度,极大地提高网络的可用性。     

有向黑白旅行商问题

黑白旅行商问题是经典旅行商问题的推广,在基于SONET技术的光纤网络设计、航线调度等领域具有广泛的应用.已有研究工作集中在无向黑白旅行商问题上.文章研究该问题的更一般形式--有向黑白旅行商问题.首先,给出了有向黑白旅行商问题的混合整数线性规划公式.与目前无向黑白旅行商问题包含指数多个约束的规划公式相比,它仅包含多项式个约束.其次,给出了一种启发式算法.实验表明,该启发式算法能够有效地求解黑白旅行商问题的实例.由于无向黑白旅行商问题是有向黑白旅行商问题的特例,故文中的结论对于求解无向黑白旅行商问题同样有效.     

基于道路网络的受限优化路径搜索算法

为刻画基于道路的景区空间相关情况,通过定义道路网络模型、道路受限距离、R-半径近邻道路等概念,提出受限的空间自相关指标及优化道路路径算法SRP,用于搜索景区路网中景点的最邻近道路及计算道路长度。利用MapInfo格式的贵州省城市主干道数据进行实验,结果表明,SRP算法能快速找到最优道路路径。     

优化路径分配的多作业机器人任务规划

提出一种优化路径分配的多机器人任务规划框架。对任务规划问题进行形式化描述,在此基础上,探讨实现优化路径分配的任务规划的关键技术,包括追索最短道路求解方法、多目标任务分配的随机化求解和概率框架的更新模型。实验结果表明,该理论框架具有可行性和实用性。     

基于最优搜索算法的自动货运线路生成

货物运输最优路线的自动生成是多属性决策理论的一种应用 ,可以用层次分析法 ( AHP)来解决决策问题。文章分析了货物运输的特性 ,结合层次分析法和最短路径问题 ( SP)探讨了一种结构比较实用的算法 :运用层次结构模型将影响货物运输线路的各个组成因素进行分解 ,通过各因素对线路的综合影响而确定该线路的代价 ;将货物运输路线的自动生成映射到图论中的最短路径问题     

计算机数控系统光滑时间最优轨迹规划

基于控制向量参数化(CVP)方法, 研究了计算机数控(CNC)系统光滑时间最优轨迹规划方法. 通过在规划问题中引入加加速度约束, 实现轨迹的光滑给进. 引入时间归一化因子, 将加加速度约束的时间最优轨迹规划问题转化为固定时间的一般性最优控制问题. 以路径参数对时间的三阶导数(伪加加速度)和终端时刻为优化变量, 并采用分段常数近似伪加加速度, 将最优控制问题转化为一般的非线性规划(NLP)问题进行求解. 针对加加速度、加速度等过程不等式约束, 引入约束凝聚函数, 将过程约束转化为终端时刻约束, 从而显著减少约束计算. 构造目标和约束函数的Hamiltonian函数, 利用伴随方法获得求解NLP问题所需的梯度.     

Reduction approaches for robust shortest path problems

We investigate the uncertain versions of two classical combinatorial optimization problems, namely the Single-Pair Shortest Path Problem (SP-SPP) and the Single-Source Shortest Path Problem (SS-SPP). The former consists of finding a path of minimum length connecting two specific nodes in a finite directed graph G; the latter consists of finding the shortest paths from a fixed node to the remaining nodes of G. When considering the uncertain versions of both problems we assume that cycles may occur in G and that arc lengths are (possibly degenerating) nonnegative intervals. We provide sufficient conditions for a node and an arc to be always or never in an optimal solution of the Minimax regret Single-Pair Shortest Path Problem (MSP-SPP). Similarly, we provide sufficient conditions for an arc to be always or never in an optimal solution of the Minimax regret Single-Source Shortest Path Problem (MSS-SPP). We exploit such results to develop pegging tests useful to reduce the overall running time necessary to exactly solve both problems.     

Distributed adaptive leader-following tracking control of networked Lagrangian systems with unknown control directions under undirected/directed graphs

This paper addresses the leader-following consensus problem of networked Lagrangian systems with unknown control directions and uncertain dynamics. For undirected graphs and directed graphs, two types of distributed control protocols are proposed without assuming that the leader's position information is linearly parameterised. It is proven that all signals in the closed-loop system are bounded, and a leader-following consensus can be achieved with the proposed corresponding protocols. These protocols are distributed in the sense that the control input for each Lagrangian system is solely based on local relative position and velocity information from its neighbourhood set and does not require additional information, e.g. acceleration or observer information of its neighbours, thus avoiding the dead-loop problem and reducing the communication burden. Simulations on networked two-link revolute joint arms are given to validate the theoretical findings.     

过必经点集且具有额外硬约束的最短路径算法

求解过必经点集的最短路径问题已有多种算法,但其应用到在具有额外硬约束限定条件的场景时存在不足。针对此类问题,提出一种基于深度优先搜索发展的随机搜索算法,由使用者依据现场情况给出数学描述,建模抽象为无向带权图表示;依据路径规划要求定义相关变量,包括路径规划的起点、终点、必经点集以及额外硬约束条件,图信息和节点信息以邻接矩阵的形式保存;搜索过程中对路径的可行性加入额外硬约束条件进行实时判定,最终获得最短路径解。实验仿真和实测结果表明,该算法能有效规避额外硬约束条件下的中间路径,生成合理的最短路径,改善相关问题的可求解性。     

基于DNA计算的层次图聚类算法

为解决使用DNA计算图聚类问题,提出一种基于DNA计算的层次图聚类算法。在分裂层次聚类中,使用DNA分子对图中顶点、边进行编码,在试管中并行产生最小生成树,根据给定阈值,通过切割树枝得到聚类结果。在凝聚聚类中使用DNA计算产生哈密尔顿路径,通过寻找最短哈密尔顿路径得到聚类结果。实验结果验证了该算法的可行性。     

粘贴与删除系统求解最短有向路的DNA计算模型

最短有向路问题是在一个有向网络中的两个指定顶点之间找出一条具有最小权的有向路,它在工程实践中具有广泛的应用。粘贴系统与删除系统是DNA计算形式模型中的两种基本模型。论文利用粘贴与删除系统的巨大并行性给出了求解图最短有向路问题的DNA计算模型及其实现算法。     

一种基于灵敏度分析的最短路可靠性评估模型

首先对最短路灵敏度分析的概念进行了拓展,然后给出了最短路灵敏度分析的基本公式。与通信网络链路实际相联系,假设图中各弧的权值是随机变量,具有独立的概率分布函数。最后基于最短路灵敏度分析基本公式,给出了一种新型的最短路可靠性评估模型。     

Solution of the input-constrained LQR problem using dynamic programming

The input-constrained LQR problem is addressed in this paper; i.e., the problem of finding the optimal control law for a linear system such that a quadratic cost functional is minimised over a horizon of length N subject to the satisfaction of input constraints. A global solution (i.e., valid in the entire state space) for this problem, and for arbitrary horizon N, is derived analytically by using dynamic programming. The scalar input case is considered in this paper. Solutions to this problem (and to more general problems: state constraints, multiple inputs) have been reported recently in the literature, for example, approaches that use the geometric structure of the underlying quadratic programming problem and approaches that use multi-parametric quadratic programming techniques. The solution by dynamic programming proposed in the present paper coincides with the ones obtained by the aforementioned approaches. However, being derived using a different approach that exploits the dynamic nature of the constrained optimisation problem to obtain an analytical solution, the present result complements the previous methods and reveals additional insights into the intrinsic structure of the optimal solution.     

On designing a shortest-path-based cache replacement in a transcoding proxy

The technology advance in network has accelerated the development of multimedia applications over the wired and wireless communication. To alleviate network congestion and to reduce latency and workload on multimedia servers, the concept of multimedia proxy has been proposed to cache popular contents. Caching the data objects can relieve the bandwidth demand on the external network, and reduce the average time to load a remote data object to local side. Since the effectiveness of a proxy server depends largely on cache replacement policy, various approaches are proposed in recent years. In this paper, we discuss the cache replacement policy in a multimedia transcoding proxy. Unlike the cache replacement for conventional web objects, to replace some elements with others in the cache of a transcoding proxy, we should further consider the transcoding relationship among the cached items. To maintain the transcoding relationship and to perform cache replacement, we propose in this paper the RESP framework (standing for REplacement with Shortest Path). The RESP framework contains two primary components, i.e., procedure MASP (standing for Minimum Aggregate Cost with Shortest Path) and algorithm EBR (standing for Exchange-Based Replacement). Procedure MASP maintains the transcoding relationship using a shortest path table, whereas algorithm EBR performs cache replacement according to an exchanging strategy. The experimental results show that the RESP framework can approximate the optimal cache replacement with much lower execution time for processing user queries.