基于QoS需求的认知无线电资源分配算法

在误比特率、总发射功率以及主用户可容忍干扰门限的约束下,提出一种基于正交频分复用的认知无线电系统多目标优化贪婪分配算法。以最小化发射功率、最小化跨频干扰及满足次用户QoS需求为优化目标,线性组合这3个目标函数,把多目标优化问题转化为单目标优化问题,采用贪婪算法实现多目标优化。仿真结果表明,该算法的系统总容量趋近于最优,在降低对主用户跨频干扰的同时,能够有效地满足次用户的QoS需求。     

认知Mesh网络中基于免疫多目标优化的频谱分配

针对认知无线Mesh网络(CWMN)的频谱分配问题,提出了一种基于免疫多目标优化的实现算法。该算法将要求解的频谱分配建模为最大化总带宽和最小化占用频谱数的多目标优化问题,设计了适合问题求解的抗体编码方式、整体克隆算子和非支配抗体选择算子。仿真实验结果表明,所提算法可以求得CWMN频谱分配问题的Pareto最优解,提高了最大化总带宽,减少了最小化占用频谱,优化了频谱分配性能。     

含有并行机器组的串行短生产线的性能分析

文中主要研究含有并行机器组的串行短生产线的生产性能,此生产线含有一个并行机器组及其上下游缓冲区.由概率守恒原理推导出短生产线的概率平衡方程,求得到短生产线的稳态概率,由此计算串行短生产线的性能指标:平均生产率和平均在制品数量.在Matlab平台下分析系统平均生产率与部分系统参数之间的关系.同时,建立短生产线的Petri网模型,采用事件调度法对短生产线进行仿真,将数值结果与仿真结果进行对比分析,说明文中以机器为中心的分析方法的有效性.     

基于多维业务的网络代价分布式优化算法

实际的通信网络是由多种网络组成的,网络代价最小化问题需要研究各个网络应当承载的业务量,然而目前网络负载均衡算法对业务分配优化问题仅考虑单网络场景.针对多网络场景,提出了四种不同网络间相互合作的业务分配问题的多维业务分配算法.该算法在考虑网络间的业务分配问题时,从网络容量、业务类型、网络覆盖范围、用户习惯和终端等几个因素综合考虑,在这些因素的约束下,通过求解网络代价最小化方程,得到了最优业务分配方案.通过对单位区域内的多网络负载场景进行仿真,验证了该算法对网络负载优化的有效性,可充分降低网络负载,适用性强.     

缓冲区有限的流水车间调度问题的启发式算法

针对缓冲区有限的流水车间调度问题,分析了目标函数的特征,及目标函数与工件空闲时间之间的关系,设计开发了启发式算法。算法将以Makespan为目标函数转化成以最小化机器空闲时间为目标函数,并以此为基础构造初始加工序列,再通过贪婪排序与插入寻优消除缓冲区受限约束并寻找问题的近优解。仿真实验结果表明,算法在求解质量和计算时间方面明显优于其他几种排序规则,并体现了目标函数表达式结构的特性及对解的适应性。     

考虑缓冲区故障的CIMS生产线可靠性模型

本文对考虑缓冲区故障的多级CIMS生产线的可靠性问题进行了研究,分析了缓冲区故障对生产线运行的影响,求出了系统稳态可用度及稳态生产率,并用一数值例子进行了说明。     

多信道无线Mesh网络信道分配算法

针对无线Mesh网络的带宽容量问题,文章通过使用无线网络干扰协议模型对无线链路的干扰进行量化,利用整数线性规划公式对信道分配问题进行描述,在信道分配的时候,应用目标函数对无线链路的信道分配进行优化,使网络总的干扰权重最小化,在此基础上提出一个信道分配的启发式算法。仿真结果表明,文章提出的算法能提高网络的吞吐量。     

集装箱码头设备配置与作业调度集成优化研究

合理配置与调度自动化集装箱码头岸桥、场桥和AGV(automated guided vehicle)等设备对提高码头作业效率,减少能耗具有重要意义.在集装箱码头缓冲区容量有限的条件下,结合AGV路径无冲突约束,建立了以最小化船舶在港时间和最小化总能耗为目标的多目标混合整数规划模型,并设计了双层遗传算法求解方法.以某市自...     

基于容量与干扰的CogWMN信道分配和路由算法

为解决认知无线mesh网络中的信道干扰问题,提出了一种基于容量与干扰的分布式信道分配和路由算法.首先根据路由度量有效地选择最低累积代价路由,再根据信道干扰容量比最小化来选择信道.仿真结果表明:所提算法与基于干扰、基于链接的算法相比,能够显著改善平均吞吐量和时延等网络参数性能.     

多级CIMS生产线的可靠性分析

本文对带有缓冲区的可修的多级 CIMS 串行生产线的可靠性问题进行了研究.用马氏过程对中间工作站及中间缓冲区的状态进行了分析,得到了生产线的稳态可用度和稳态生产率的解析式,并用一个例子进行了说明.     

Two approaches for solving the buffer allocation problem in unreliable production lines

This paper presents an integrated approach to solve the buffer allocation problem in unreliable production lines so as to maximize the throughput rate of the line with minimum total buffer size. The proposed integrated approach has two control loops; the inner loop and the outer loop. While the inner loop control includes an adaptive tabu search algorithm proposed by Demir et al. [8], binary search and tabu search are proposed for the outer loop. These nested loops aim at minimizing the total buffer size to achieve the desired throughput level. To improve the efficiency of the proposed tabu search, alternative neighborhood generation mechanisms are developed. The performances of the proposed algorithms are evaluated by extensive computational experimentation, and the results are reported.     

高吞吐量的核心无状态公平队列算法

提出了一种优化的核心无状态公平队列凋度算法(xCSFQ),在CSFQ的基础上,根据缓冲区占用率和数据流到达速率决定丢包概率,缓存管理上采用基于CHOKC原理的机制进行缓存管理,解决了CSFQ链路利用率低的问题,提高了带宽在UDP流和TCP流之间分配的公平性,最后对算法进行了仿真分析。     

Algorithms for determining capacities of individual buffers in assembly/disassembly systems

We deal with a buffer allocation problem of assembly/disassembly (AD) systems with a finite buffer capacity. The problem is to determine capacities of individual buffers for a given total available capacity of buffers with the objective of maximizing throughput rate. We first present an algorithm (BA-G) in which a conventional gradient search is used for finding an initial solution and a two-optimization procedure is used for improving the initial solution. Since this algorithm may require an excessive computation time, especially when a procedure for performance evaluation employed in the algorithm takes a long computation time, a new algorithm (BA-P) is developed in which a sophisticated procedure is used for finding an initial solution. In this procedure, capacities of individual buffers are determined based on the efficiency of their upstream and downstream machines. Results of computational experiments show that the latter algorithm gives the same solutions as those obtained by the former algorithm in much shorter time.     

Buffer allocation in unreliable production lines using a knowledge based system

The optimization of production lines performance is a problem of great complexity and, therefore, of significant research interest. The problem may involve the optimization of many conflicting objectives, such as increasing throughput and reducing work-in-process time. The majority of existing studies have used various heuristics and search methods based on operations research. These methods have been proved to be computationally inefficient, especially for large production lines. This paper presents ASBA2, a knowledge based system that determines near optimal buffer allocation plans, with the objective of maximising production lines throughout. The allocation plan is calculated subject to a given amount of total buffer slots, in a computationally efficient way. ASBA2 operates in close cooperation with a simulation method, which provides ASBA2 with performance measures concerning production line behaviour. Moreover, to evaluate results provided by ASBA2, we have utilized an exact numerical algorithm for calculating the throughput of unreliable production lines.     

Efficient combined immune-decomposition algorithm for optimal buffer allocation in production lines for throughput and profit maximization

Adequate allocation of buffers in transfer lines is crucial to the optimization of line throughput and work in process (WIP) inventory. Their optimal allocation is subject to specific constraints, associated costs, and revenue projections. In this paper, we implement a combined artificial immune system optimization algorithm in conjunction with a decomposition method to optimally allocate buffers in transfer lines. The aim of the buffer allocation problem (BAP) is to achieve optimal system performance under buffers space constraints. Maximizing line throughput does not necessarily achieve maximum profit. In this study the immune decomposition algorithm (IDA) is used to determine optimal buffer allocation for maximum line throughput and maximum line economic profit.Results of extensive series of tests carried out to compare, in production lines with different characteristics, the performances of the proposed method and those of other algorithms are presented.     

无线协作网络中的能量有效性中继选择算法

研究了无线协作网络中的中继选择问题,允许中继具有缓存数据的能力,提出了一种带有buffer的能量有效性中继选择算法,以延长网络生命周期并提高系统吞吐量。该算法综合考虑链路信息,中继的队列状态以及节点的剩余能量信息,通过加权效用公式选择最优接收数据中继与最优发送数据中继。考虑源节点与中继节点间的功率分配,以降低因源节点到中继节点以及中继节点到目的节点间的信道速率不一致所引起的系统丢包率。仿真实验结果表明,该算法有效地延长了网络的生命周期,随着中继个数的增加网络吞吐量有明显的提高,考虑功率分配后,有效降低了系统丢包率。     

数据库管理系统多缓冲池的配置及其多次划分自调优算法

本文针对数据库管理系统中缓冲区的特殊重要地位,介绍了多缓冲池的配置及自调优的概念。将缓冲区分为数个独立的缓冲池,为不同性质的数据库对象分别建立独立的缓冲池 ,也为不同的负载提供最佳的配置方式,能够减少不同负载下的i/os时间,提高吞吐率。本文介绍了多缓冲池配置的模型,并基于此模型提出了多缓冲池的多次划分自调优算法。     

一种改进的RED算法

本文就目前路上器中如何实现数据流隔离和公平分配带宽进行了探讨，首先研究了Sally等人提出的RED算法，指出其缺陷，并根据TCP的有效吞吐率公式，提出了一种改进的RED算法，它可以实现更好的公平性，仿真结果验证了算法的有效性。     

部分信道状态信息下MIMO-OFDM的跨层资源分配算法

针对跨层多用户多输入多输出-正交频分复用（MIMO-OFDM）系统,以系统最大吞吐量为目标,给出一种基于部分信道状态信息的跨层资源分配算法。该优化问题设计的目标函数包括功率限制、传输速率、子载波占用、不同业务的服务质量需求与数据链路层的队列状态信息等约束条件。在数据链路层存在有限缓存条件下,通过均值反馈模型描述信道状态信息的反馈过程,推导出相应的跨层资源分配准则。仿真结果表明,所提算法与现有方案相比,满足了不同业务用户的QoS要求,并获得了好的吞吐率,降低了丢包率。     

基于缓存利用率检测的调度算法

针对目前卫星通信网络中虚拟信道调度与缓存管理算法间的孤立性,提出一种基于缓存利用率检测的调度算法。该算法通过对星上缓存利用率和紧迫度的分析,由调度函数指示完成相应虚拟信道的调度。采用OPNET对该调度算法进行仿真与对比分析,结果表明缓存利用率检测调度算法在保证一定吞吐量的前提下,能有效降低数据丢失率和延时,避免因不公平性导致的低优先级业务的“饿死”现象。