基于云自适应遗传算法的NoC路径分配研究

路径分配是NoC设计流程中的两个关键步骤之一;路径分配的结果对NoC系统的性能尤其是通讯延时有着很重要的影响;多约束条件下的NoC路径分配问题是NP完全问题,要求出其最优解比较困难,目前常用的方法是利用启发式算法求得其较优解;文中提出一种基于云自适应遗传算法的NoC路径分配解决方案,该算法利用云模型对传统遗传算法加以改进,采取新的方法自动调整遗传算法过程中的交叉概率pc和变异概率pm,将适应度与云模型的3个参数Ex、En、He相互结合,从而达到优化遗传算法的目的;将此算法应用于2D-Mesh拓扑结构的NoC中,以平衡链路负载和联合优化为实验目标,以优化静态通讯分配结果;实验证明,文章所采取的算法在平衡链路负载和联合优化方面均取得了良好的效果。     

Register allocation for write activity minimization on non-volatile main memory for embedded systems

Non-volatile memories are good candidates for DRAM replacement as main memory in embedded systems and they have many desirable characteristics. Nevertheless, the disadvantages of non-volatile memory co-exist with its advantages. First, the lifetime of some of the non-volatile memories is limited by the number of erase operations. Second, read and write operations have asymmetric speed or power consumption in non-volatile memory. This paper focuses on the embedded systems using non-volatile memory as main memory. We propose register allocation technique with re-computation to reduce the number of store instructions. When non-volatile memory is applied as the main memory, reducing store instructions will reduce write activities on non-volatile memory. To re-compute the spills effectively during register allocation, a novel potential spill selection strategy is proposed. During this process, live range splitting is utilized to split certain long live ranges such that they are more likely to be assigned into registers. In addition, techniques for re-computation overhead reduction is proposed on systems with multiple functional units. With the proposed approach, the lifetime of non-volatile memory is extended accordingly. The experimental results demonstrate that the proposed technique can efficiently reduce the number of store instructions on systems with non-volatile memory by 33% on average.     

基于最大加权独立集的频谱分配算法

动态频谱接入技术允许认知用户接入未授权的频谱,可以有效地提高频谱资源的利用率。频谱分配算法的时间开销和公平性是算法优劣的主要评价标准。本文从图论着色模型出发,构建了着色算法的评价体系及优化目标。针对用户间的公平性与分配的时间开销问题,在极大独立集的基础上提出了基于加权最大独立集的着色算法,获得了接近于最优的用户公平性,且该算法的时间开销等于信道数,与认知用户的数目无关。仿真分析验证了算法的正确性。     

车联网基于信任度的RSU识别及资源分配算法

在车联网中,由于部分路侧单元（RSU）的位置比较偏远,无法得到网络管理员的及时维护,可能遭到攻击,变为不可信任的路侧单元,降低了车辆的通信质量和网络能效.为了有效地识别RSU的可靠性,提出了一种基于信任度的路侧单元识别及资源分配算法,将路侧单元识别、传输模式的选择和功率分配联合建模为网络能效的优化问题,并分成3个子优化问题,分别求解.首先,采用基于信任度的RSU识别算法,识别出可信任和不可信任的路侧单元;其次,优化车辆资源块配置和链路选择;最后,通过次梯度算法优化传输功率,最大化网络能效.理论分析和仿真结果表明,所提算法具备较低的复杂度,可以达到较高的路侧单元识别准确度,并有效地提升网络总能效.     

基于时空特性以及需求响应的DG和EV充电站多目标优化配置

针对可再生分布式电源(DG)及电动汽车(EV)大规模接入给配电网带来的用电量增长以及电压波动问题,提出一种基于时空特性以及需求响应的DG和EV充电站多目标协调优化配置方法.通过提取城市路网的拓扑结构,监测路网流量,基于交通规划软件TransCAD进行起讫点(OD)矩阵反推,构建出行概率矩阵以描述用户的出行特性;基于蒙特卡洛方法模拟EV的时空分布特性,考虑EV、DG与常规负荷的时序特性,并基于改进K-means算法构建风-光-负荷的典型运行场景;兼顾电网侧与用户侧,以综合效益、系统负荷波动以及充电耗时成本为目标,构建DG和EV充电站的多目标联合配置模型,并采用改进粒子群优化算法进行求解.结合IEEE 33节点配电网与某城区主干道路网模型进行仿真分析,结果验证了所建模型的有效性与可行性.     

UCC项目总承包工程建设的过程管理

由成都建筑材料工业设计研究院有限公司(简称成都院)和中国建材装备有限公司组成联合体总承包的UCC 10 000 t/d熟料水泥生产线,成都院负责提供合同范围内所有的工程设计、核心技术及核心设备、现场管理、人员培训、生产线达标考核,并具体负责实施和完成所有的土建及安装工程。在总承包工程建设的过程管理中,成都院以设计为灵魂,贯彻了"工艺流程顺畅,总图布局合理,系统配置先进可靠,合理节省投资"的设计理念;成都院克服了要求高、工期短、气候条件恶劣、国外施工人员管理难度大、功效低等重重困难,按时、保质保量、安全地完成了土建、安装、调试和试车任务;2007年4月26日,该生产线一次性通过业主的达标考核。我们的经验是:(1)有专业设计院全面介入的工程总承包是项目顺利进行的可靠保证;(2)参与建设的相关单位要相互信任、相互配合、目标一致;(3)工程建设管理科学化、人性化很重要。该项目的成功建设,使成都院总包工程建设的过程管理更加正规化、合理化和科学化。     

Fuzzy arithmetic based reliability allocation approach during early design and development

During early design and development stages, every engineering system has to meet its specific reliability goals. The target reliability of the system is achieved through application of an effective reliability apportionment technique to its subsystems. There are various traditional methods exist to perform the reliability allocation based on engineering factors that are assessed in a subjective manner. The conventional reliability allocation approach requires the assessment of factors like complexity, cost, and maintenance. This may not be realistic in real applications if they are assessed in a crisp manner by the domain experts of their varied expertise and background.In this paper, we treat allocation factors as fuzzy numbers, which are evaluated in fuzzy linguistic terms. As a result, fuzzy proportionality factor scales are proposed for the subsystems. In order to accomplish fuzzy division to evaluate the fuzzy proportionality factor, an approximation method based on linear programming for trapezoidal fuzzy numbers is also proposed in this paper. For the evaluation of weighting factors from fuzzy proportionality factors, centroid method of defuzzification is being employed. The allocated reliability of each subsystem is computed with the help of weighting factor thereafter. An example is provided to illustrate the potential application of the proposed fuzzy based reliability allocation approach.     

A hybrid vendor managed inventory and redundancy allocation optimization problem in supply chain management: An NSGA-II with tuned parameters

In this research, a bi-objective vendor managed inventory model in a supply chain with one vendor (producer) and several retailers is developed, in which determination of the optimal numbers of different machines that work in series to produce a single item is considered. While the demand rates of the retailers are deterministic and known, the constraints are the total budget, required storage space, vendor's total replenishment frequencies, and average inventory. In addition to production and holding costs of the vendor along with the ordering and holding costs of the retailers, the transportation cost of delivering the item to the retailers is also considered in the total chain cost. The aim is to find the order size, the replenishment frequency of the retailers, the optimal traveling tour from the vendor to retailers, and the number of machines so as the total chain cost is minimized while the system reliability of producing the item is maximized. Since the developed model of the problem is NP-hard, the multi-objective meta-heuristic optimization algorithm of non-dominated sorting genetic algorithm-II (NSGA-II) is proposed to solve the problem. Besides, since no benchmark is available in the literature to verify and validate the results obtained, a non-dominated ranking genetic algorithm (NRGA) is suggested to solve the problem as well. The parameters of both algorithms are first calibrated using the Taguchi approach. Then, the performances of the two algorithms are compared in terms of some multi-objective performance measures. Moreover, a local searcher, named simulated annealing (SA), is used to improve NSGA-II. For further validation, the Pareto fronts are compared to lower and upper bounds obtained using a genetic algorithm employed to solve two single-objective problems separately.     

许昌市水资源多模式联合调度与合理配置

水资源短缺是制约城市经济社会发展的重要因素,合理配置和有效利用有限的水资源是解决水资源供需矛盾的有效途径。以许昌市国家水生态文明试点城市建设为例,在分析水资源开发利用现状的基础上,运用定额法对需水量进行预测。以多年平均水资源量为基础,2011年作为研究基准年,根据水资源取用方式、工程方案及各种水量需求等,利用MIKE BASIN建立水资源配置模型,对许昌市水资源供需平衡进行模拟,通过三次供需平衡分析,得到不同规划水平年水资源供需配置方案,最终达到水资源供需平衡,使有限的水资源发挥最大效益。研究结果表明,本地水资源结合南水北调、引黄调蓄、中水回用等多模式联合调度,可以满足许昌市中长期经济社会可持续发展用水需求,对未来许昌市水资源可持续利用具有重要的指导意义。     

基于非负矩阵分解的水量分配方案后评价

提出了水量分配方案后评价指标体系,建立了基于非负矩阵分解的水量分配方案后评价模型,并以1983年国务院批复的引滦水量分配方案为研究对象进行了水量分配方案诊断式后评价。该方法利用非负矩阵分解算法将指标矩阵最大程度分解为基向量和权向量,根据权向量元素的数值对水量分配方案进行评级,根据基向量元素的数值判断评价指标的实施状况。通过对引滦水量分配方案质量、实施过程、实施效果和可持续性的调查分析,得出方案综合后评价结果为优,但在来用水可持续性、对水环境影响及水质目标保证率等方面需加以改进。评价结果表明,基于非负矩阵分解原理的后评价方法评价效果较好,可为水量分配方案等项目的后评价提供科学依据。