BDCP:一个有效的相关任务调度算法

表调度算法ＢＤＣＰ采用动态关键路径技术并均衡考虑关键路径结点和非关键路径结点,使得对相关任务图调度长度影响最大的就绪得结点能够被优先调度,从而极大地缩短了调度长度。分析和实验结果表明,该算法要明显优于ＭＣＰ和ＥＴＦ算法。     

面向无人机物流的分布式任务调度

为提高无人机物流任务调度系统的实时性、可靠性和扩展性,本文提出一种面向通用航空无人机物流的分布式自主任务调度系统,并阐述了该系统的概念、架构、机制和运行模式;为实现物流任务的高效分配,适用于常规物流及紧急物流任务,结合集中调度及边缘自主两种调度模式.实验证明:该系统可为通用航空无人机物流提供一种有效途径,成为未来无人机物流的主要调度模式之一.     

可信分布式实时系统的面向方面的形式化方法

形式化方法具有精确数学含义的科学研究和验证方法,是建立在数学基础上的,可信分布式实时系统开发过程中的时间分析是非常复杂的,涉及到不同的方面,需要考虑很多东西,不同的可信分布式实时系统具有不同的时间性需求,不能用一种开发方法进行分析、设计和实现,由于形式化方法具有严谨、可数学分析、证明、完整性、一敌性、无二义性和精确性等特性,可以根据系统开发的不同方面采用不同的形式化语言进行分析、设计和实现,然后再把这些方面编织应用到系统中去,来完成它在系统中特定的作用,因此形式化方法已经成为人们深入研究的一个领域。     

基于DPSO算法的并行测试任务调度

为解决并行测试任务调度复杂、难以优化的难题,利用惯性因子动态调整的粒子群算法(dynamic particle swarm optimization,DPSO)建立任务间存在约束关系的并行测试任务调度模型,给出模型求解算法,并通过仿真实验验证该模型的有效性和DPSO算法应用于并行测试任务调度的可行性。     

一种分布式联合输入输出排队结构及其调度算法

分析论证了分布式联合输入输出排队(DCIOQ)结构模拟输出排队调度的充分条件,提出了一类满足这一条件的调度算法,并从工程实现的角度给出了这类算法的一种简易实现方案。与传统方案相比,该方案不仅具有高的带宽利用效率和良好的调度公平性,而且工程实现复杂度较低。     

USAN算法在实时系统中的实现

介绍USAN(Univalue Segment Assimilating Nucleus即吸收同值核区)算法在实时系统上的应用。应用USAN模板对图像扫描,并且对扫描后的数据做方向识别,获得目标上的角点特征,从而得到以角点为跟踪点的跟踪算法。此算法由于其跟踪点稳定,不受随机噪声的影响,因而可以大大提高跟踪精度,在实际应用中获得较好的效果。     

基于改进A*算法的仓储物流移动机器人 任务调度和路径优化研究

为解决仓储物流中移动机器人执行订单任务过程中,调度系统难以快速准确地进行任务分配,且搬运路线并非最短最优路线的问题,根据移动机器人的运动方式和订单任务要求,构建具有可重构性的仓库空间模型和栅格地图模型,通过建立数学模型求解订单任务最短完工时间分配问题,改进传统A^*算法中3种常用距离算法的不足,并提出复杂对角线距离算法进行路径规划仿真。仿真结果表明,上述方法实现总任务完工时间最短的任务分配,使路径规划搜索节点数减少30%,路径长度缩短20%。     

高阶数字滤波器分布式算法结构比较

基于FPGA,对高阶FIR滤波器两种算法--\"基于查找表(LUT)的分布式算法\"和\"改进的分布式算法\"的功能及结构差异进行类比.\"改进的分布式算法\"是对\"基于LUT分布式算法\"在减少存储器技术上的改进.对于一个高阶滤波器来说,\"改进的分布式算法\"比\"基于LUT的分布式算法\",需要更少的存储器和系统资源.减少存储器使用的递归反复技术极大地增加了在FPGA平台上可实现的滤波器阶数的最大值.\"改进的分布式算法\"不仅节省了使用的电子器件数量,而且还平衡了FPGA硬件资源中逻辑单元(LE)和存储器的使用.从FPGA的执行结果可以确定,\"改进的分布式算法\"可以实现一个1024抽头的FIR滤波器,且比\"基于LUT的分布式算法\"节省更多系统资源.     

基于遗传蚁群算法的并行测试任务调度与资源配置

针对多UUT(Unit Under Test)并行测试任务调度与资源配置问题,提出了一种遗传蚁群融合算法.应用遗传蚁群融合算法能快速、准确地寻找到具有最大成本效率的多UUT并行测试资源配置和任务序列.建立了多UUT并行测试任务资源描述的数学模型,分析了多UUT测控资源合并的条件,得出最短并行测试时间基础上的最少资源需求,给出了成本效率的定义,设计了一种满足多UUT并行测试任务调度的基因编码方法和路径选择方案.算法初期利用遗传算法的快速收敛性,为蚁群算法提供初始信息素分布,蚁群算法采用双向收敛的信息素反馈方式,避免了对参数的依赖,减少了局部收敛性,加快了收敛速度.实例表明,该算法能很好地解决多UUT任务资源最优调度与配置问题.     

分布式存储平台的设计与实现

在数字信息爆炸的时代,社会对于信息的存储需求量急剧增加,本文针对传统单机存储方式的不足,提出了设计分布式存储平台的思路,以此为高效的存储和获取信息提供又一途径。主要介绍了分森式存储平台的优势与设计原理、平台的整体设计和关键算法及其主要模块交互与关键流程的实现。     

Self-adaptive dynamic scheduling of virtual production systems

To enhance the agility of virtual production systems (VPSs) under today's dynamic and changing manufacturing environment, a self-adaptive dynamic scheduling method based on event-driven is proposed for VPSs in this paper. This method is composed of the mechanisms and algorithm of self-adaptive dynamic scheduling. In the mechanisms, the dynamic events faced by VPSs are determined through users’ inputs or supervisory controllers’ detections, the local effects made on the schedule are analysed according to the dynamic events, and the self-adaptive measures and rules are specified correspondingly. To implement the dynamic scheduling of VPSs under the guidance of self-adaptive rules, a modified heuristic rescheduling algorithm is proposed for affected operations. A case study illustrates that the proposed method can well accomplish the dynamic scheduling of VPSs in a self-adaptive manner.     

OFDMA系统中支持混合业务的跨层调度算法

针对正交频分多址接入(OFDMA)系统下行链路的混合业务调度问题,提出了一种基于队列等待时间的跨层调度算法.该算法联合利用了MAC层的队列等待时间与物理层的信道状态信息作为调度参数,通过队列等待时间反映用户的服务质量要求,并利用多用户分集增益提高系统性能;针对实时和非实时用户的不同服务质量要求,在队列等待时间的计算上采取了不同的策略;在子载波的分配过程中根据分配状态及时更新队列等待时间,使资源的利用更为有效.仿真结果表明,提出的算法可显著降低实时用户的平均时延和最大延时违反概率,同时保证了非实时用户的吞吐量需求,能够有效地支持下一代网络中混合业务的多种服务质量要求.     

Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm

We consider a joint decision model of cell formation and task scheduling in cellular manufacturing system under dual-resource constrained (DRC) setting. On one hand, machines and workers are multi-functional and/or multi-skilled, and they are grouped into workstations and cells. On the other hand, there is a processing sequence among operations of the parts which needs to be dispatched to the desirable workstations for processing. Inter-cell movements of parts can reduce the processing times and the makespan but will increase the inter-cell material handling costs. The objective of the problem is to minimise the material handling costs as well as the fixed and operating costs of machines and workers. Due to the NP-hardness of the problem, we propose an efficient discrete bacteria foraging algorithm (DBFA) with elaborately designed solution representation and bacteria evolution operators to solve the proposed problem. We tested our algorithm using randomly generated instances with different sizes and settings by comparing with the original bacteria foraging algorithm and a genetic algorithm. Our results show that the proposed DBFA has better performance than the two compared algorithms with the same running time.     

基于改进粒子群算法的分布式天线系统跨层功率分配方案

结合数据链路层的队列状态信息和物理层的信道状态信息定义了系统的吞吐量系数和公平性系数,建立了分布式天线系统跨层功率分配的离散速率集优化模型。对粒子群优化算法的初始群体产生、粒子更新等步骤进行了改进,形成了改进粒子群算法(IMPSO)。利用IMPSO进行了动态功率分配和跨层优化。数值仿真结果表明,IMPSO能够取得很好的队列时延性能,选取不同的权重可对系统吞吐量性能和公平性性能产生重要影响,IMPSO获得的系统吞吐量性能和公平性性能较之功率固定分配算法(AP)均有较大幅度的提高。     

全复用多小区系统下行链路用户调度与功率分配

对全复用多小区系统下行链路用户调度与功率分配问题进行了研究,提出了一种半分布式的用户调度与功率分配方案.首先,各小区根据自身所辖用户的信道与干扰信息,采用最大信干噪比准则进行用户调度,然后各基站将所调度用户的信息上报给中央资源控制器,最后中央资源控制器基于最速下降法的思想,采用贪婪功率分配(GPA)算法为各用户分配相应的发射功率.所提方案利用小区之间的相互协作有效地弱化了小区间干扰,与现有方法相比获得了更好的吞吐量性能和更高的功率效率.     

The extended resource task network: a framework for the combined scheduling of batch processes and CHP plants

The issue of energy has emerged as one of the greatest challenges facing mankind. In an industrial perspective, the development of site utility systems (generally combined heat and power (CHP) systems) for the generation and management of utilities provides a great potential source for energy savings. However, in most industrial sites, a master–slave relationship usually governs this kind of system and limits the potential operating capacity of CHP. To improve the decision-making process, Agha et al. (2010. Integrated production and utility system approach for optimising industrial unit operation. Energy, 35, 611–627) have proposed an integrated approach that carries out simultaneous and consistent scheduling of batch production plants and site utility systems. The modelling of the problem relies on a mixed integer linear programming (MILP) formulation. Nevertheless, although it is a powerful mathematical tool, it still remains difficult to use for non-expert engineers. In this framework, a graphical formalism based on existing representations (STN, RTN) has been developed: the extended resource task network (ERTN). Combined with an efficient and generic MILP formulation, it permits various kinds of industrial problems, including production and consumption of utility flows to be modelled homogenously. This paper focuses on the semantic elements of the ERTN formalism and illustrates their use through representative examples.     

Group scheduling in flexible flow shops: a hybridised approach of imperialist competitive algorithm and electromagnetic-like mechanism

This paper applied a novel evolutionary algorithm, imperialist competitive algorithm (ICA), for a group scheduling problem in a hybrid flexible flow shop with sequence-dependent setup times by minimising maximum completion time. This algorithm simulates a social-economical procedure, imperialistic competition. Initial population is generated randomly and evolution is carried out during the algorithm. Firstly individuals, countries, are divided into two categories: imperialists and colonies. Imperialist competition will occur among these empires. This competition will increase some empires authority by ruining a weak empire and dividing its colonies among others. Electromagnetic-like mechanism concepts are employed here to model the influence of the imperialist on their colonies. The algorithm will continue until one imperialist exists and possesses all countries. In order to prevent carrying out extensive experiments to find optimum parameters of the algorithm, we apply the Taguchi approach. The computational results are compared with the outstanding benchmark on the flow shop scheduling problem, random key genetic algorithms (RKGA), and it shows superiority of the ICA.     

分布仿真系统HLA联邦快速开发包的设计与实现

为提高高层体系结构(HLA)联邦开发的快捷性、易用性、可重用性及节约成本,对其运行支撑环境(RTI)接口进行了封装,结合数据公布订购自定义配置文件和MAP容器,设计并实现了封装的仿真接口包(SPI).首先,给出了SPI包的框架设计、功能分解结构、时序逻辑及函数接口定义,然后设计了仿真应用数据类的具体规范、联邦可执行文件XML和邦元公布订购数据的初始化配置文件,阐述了基于SPI的联邦快速开发步骤,最后用一个简单实例验证SPI.实验表明:相比现有的联邦编程开发软件,SPI简单高效,用户可自行设计并轻松上手,降低了开发成本,满足了特定的仿真需求.