基于发车时刻表的单线公交组合调度模型

针对目前全程车和大站快车的单线公交组合调度模型中对乘客的分类及滞站乘客乘车处理方法的不足,分3个步骤对模型进行了补充:首先,系统地探讨了乘客的构成及转化关系,并基于滞站乘客等车数、滞站原因及目的站距离提出一种处理滞站乘客乘车的方法,并以此方法计算滞站乘客等车的时间成本;其次,通过发车车型、模式和间隔的变量组合构建发车时刻表,进而以此表的信息为基础推算运营时刻表的各项变量,从而计算出公交服务各项指标及乘客和车辆的相关成本;最后,根据问题特征,应用最大最小蚁群系统算法求解模型。结合实例,对比分析了给定配车数和限定时间段内4种调度策略的发车时刻表最优解及相应最优解的公交服务指标和相关成本。实验结果表明,采用间隔不定的组合调度策略能够使车辆均衡分配站点客流,最大限度地降低乘客的时间成本及车辆耗燃成本。     

遗传-牛顿算法在公交智能调度中的应用

针对公交公司需要解决的典型问题公交车辆的优化调度,提出了一种遗传算法与牛顿算法相结合的智能优化算法;并用该混合算法对调度模型进行优化;首先在兼顾公交公司与乘客双方利益的情况下,建立了以发车间隔时间为决策变量的公交车优化调度模型,再利用遗传算法对决策变量进行优化,然后用牛顿法对其优化的结果进行深一步的搜索,使其优化结果精度提高;仿真结果表明,该混合算法比标准的遗传算法更有效地提高公交车辆运营效率并降低其费用成本.     

考虑分时客流量分布的公交车节能调度

公交车的合理调度可以最大限度的节约能源,提高公交车资源利用率.当前的车辆调度都是以已经发生拥堵为前提条件,以被动式的应对为主,模型建立以存在拥堵为前提条件,模型只是考虑了拥堵状态下的车流的流动性和不稳定性的条件,没有充分考虑拥堵前的不同时段车辆拥堵概率因素,以被动的调度方式解决问题,缺陷明显.提出了采用分时客流量分布统计预测的公交车节能调度方法.采集行车路线不同时段的乘客数量相关数据进行有效性评估和预测,进而确定需要派出的公交车形式、数量和间隔时间,在考虑时间因素下,完成车辆调度,优化调度模型.实验结果表明,利用优化算法进行公交车调度,能够极大地节约公交车能源,提高满载率和乘客的舒适度,实现公交车的最优调度.     

改进的蚂蚁算法车辆运行调度算法研究

研究车辆调度优化问题,考虑时间能合理安排运输线路.针对传统的蚁群算法收敛速度慢、易陷于局部最优、影响优化调度线路识别等缺陷,提出了一种改进的蚂蚁算法车辆调度优化方法模型.对城市车辆调度建立优化数学模型,将车辆运行调度归并为制造系统中的FLOWSHOP调度问题,构建一种动态开放的车辆调度系统优化模型,并采用改进的蚂蚁算法对数学模型进行仿真.仿真结果表明,提出的新的算法不仅能有效的求解车辆调度优化模型,可以快速得到近似最优解,而且计算机复杂度较低,收敛速度较快,是一种有效地车辆调度优化手段.     

粒子群优化算法在公交车智能调度中的应用

运营车辆的智能排班是公交车辆智能调度需要解决的问题之一,关系到公交企业的经济效益与社会效益。采用兼顾公交公司与乘客双方利益的公交车辆调度模型,将带收缩因子和线性递减惯性权重的粒子群优化算法（W-K-PSO）应用到公交智能排班中。实例仿真结果表明该算法具有比其它优化算法更好的效率,是解决公交车智能调度问题的一个有效方法。     

一种需求响应参与下风电储能系统调度方法的研究

针对风电并网对电力系统稳定性的不利影响,论文将储能系统和需求响应引入含风电的电网优化调度中.首先以系统最低发电成本为调度目标,以日前预测和实时风能预测作为随机变量,将需求响应和储能系统分别引入需求侧和发电侧,同时通过两阶段调度,构建风电储能系统的两阶段调度优化模型.其次利用粒子群优化算法对模型进行求解.应用场景分析的结构表明,所提调度方法采用粒子群优化算法可以较好求得模型的全局最优解;通过储能系统和需求响应的引入可以提高主动配电网的风电利用效率,降低发电成本.     

大型物流车辆配送线路自适应调度方法

为了有效提高物流配送车辆的利用率,降低配送车辆的空载率及物流运输成本,需要对大型物流车辆配送线路自适应调度方法进行研究。当前方法多是采用通过对物流车辆配送过程中的调度与路径选择进行分析,建立多类型的物流配送车辆调度模型,并构建改进后的遗传算法,对物流调度模型的算法效率以及计算时间和复杂度进行优化,以获取物流车辆配送调度问题的最优解,但该方法存在过程较为繁琐的问题。为此,提出一种大型物流车辆配送线路自适应调度方法。该方法首先建立物流车辆配送线路调度问题的数学模型,为实现自适应调度方法对数学模型进行优化求出最优解,利用蚁群算法对物流车辆配送调度数学模型的最优解进行优化,获取最优路径的适应度初始化蚁群算法的各客户点之间的信息素,从而得出了优化的最优路径;以优化的最优路径完成对大型物流车辆配送线路自适应调度。仿真实验表明,利用蚁群算法不仅加快了物流配送路线调度优化问题求解的速度,降低了物流运输的成本,而且获取了最优解的概率,比其他调度算法具有更明显的优势。     

改进布谷鸟算法的快速公交组合调度优化研究

为了进一步优化快速公交调度，研究了全程车，区间车、大站快车的组合调度模式。从公交公司和乘客双方利益的角度出发，考虑不同发车模式间的乘客换乘以及超车现象，建立以发车间隔与发车模式为决策变量的快速公交组合调度优化模型。设计并改进具有动态步长和发现概率的布谷鸟算法，以兰州市快速公交1号线路为例进行仿真，求得最优解和次优解的发车间隔与发车模式。结果表明，最优方案和次优方案相比优化前的总成本分别降低18.71%和15.7%;另外，在求解模型时，改进的布谷鸟算法相比遗传算法和基本的布谷鸟算法能快速收敛，验证了上述模型和算法的可行性与有效性。     

交叉口信号实时滚动优化模型及算法

为了合理控制单交叉口交通流并且优先公交,建立可变相序的实时滚动优化模型.该模型将公交优先嵌入优化控制,对每辆公交车实时分配权重系数,以交叉口社会车辆和公交车辆的人均延误最小为目标,优化确定相位序列和相位长度.通过跳相来实现相序优化,运用改进的遗传算法来求解.具体实例表明,可变相序的实时滚动优化模型能有效地减少系统的人均延误,并能在尽量减小对社会车辆的影响下实现公交优先.     

基于改进遗传—模拟退火算法的公交排班优化研究

结合公交车辆调度自身的特点,兼顾公交公司与乘客双方的利益,建立了公交排班优化模型,以发车时刻为基因变量进行编码,对两个相邻的发车间隔之差、最大最小发车时间间隔、乘客的满载率等条件进行约束限制,提出了基于改进的遗传—模拟退火算法;对该模型进行优化求解,克服了传统优化算法的缺陷,提高了优化设计过程的求解效率。通过仿真实验得到了利用改进的遗传—模拟退火算法进行求解的不均匀发车时刻表。结果表明,改进的遗传—模拟退火算法能够在公交智能排班优化问题的巨大搜索空间中可靠地找到近似最优解,大大提高了计算效率。     

网络数据动态传输与存储安全自动监测系统设计

为了提高网络数据动态传输与存储安全自动监测能力,进行监测系统优化设计,提出基于负载均衡调度和嵌入式总线传输控制的网络数据动态传输与存储安全自动监测系统设计方法。构建网络数据动态传输的信道均衡调度模型,采用随机线性均衡控制方法进行网络数据动态传输与存储过程中的信道自适应调度,提取网络数据动态传输过程中的模糊关联规则,采用自适应的链路转发控制方法进行网络数据动态传输与存储的安全监测和负载均衡调度。在嵌入式总线协议下进行网络数据动态传输与存储安全自动监测系统的软件开发设计。仿真结果表明,采用该方法进行网络数据动态传输与存储安全自动监测的稳定性较好,自适应控制能力较强,降低了网络数据动态传输的误比特率。     

基于动态规划的城市公交运营管理系统研究

行车作业安排算法的时间复杂度和空间复杂度往往随着数据量的增加而急剧增大。利用动态规划算法,以司机组和公交车组的优先级向量作为动态规划的状态,推导并求解行车作业安排的状态转移方程组。通过使用GIS技术和动态规划算法,设计并实现信息化、透明化的城市公交运营管理系统,该系统具有司机信息管理、线路管理、权限管理、公交车信息管理...     

基于云网格集成调度的防拥堵车辆路径规划算法

在道路交通路网中,车辆拥堵问题是流量与路网结构之间相互作用的一个复杂动态过程,通过车辆路径规划,实现对路网网格集成调度,从而提高路网通行吞吐量。传统方法采用并行微观交通动态负载平衡预测算法实现车辆拥堵调度和车辆路径规划,不能准确判断路面上的车辆密度,路径规划效益不好。提出一种基于云网格集成调度的防拥堵车辆路径规划算法,即构建基于Small-World模型的云网格路网模型,采用RFID标签信息进行路况信息采集,实现交通网络拥堵评估信息特征的提取,采用固有模态函数加权平均求得各车道的车辆拥塞状态函数,对所有车道内车辆密度取统计平均可获得簇内的车辆密度。设计交通路网拥堵检测算法来对当前个体道路信息进行一维邻域搜索,从而实现车辆路径规划控制目标函数最佳寻优。通过动态博弈的方式求得车辆防拥堵路径的近似最优轨迹,实现路径规划算法的改进。仿真结果表明,该算法能准确规划车辆路径,实现最优路径控制,从而提高严重拥堵路段的车流速度和路网吞吐性能,性能优越。     

A multiprocessor bus design model validated by system measurement

An accurate and efficient model of a commercial multiprocessor bus is developed. Four important characteristics of the bus design are modeled: asynchronous memory write operations; in-order delivery of responses to processor read requests; priority scheduling of memory responses; and upper bounds on the number of outstanding processor requests. A two-level hierarchical model employing both Markov chain and mean value analysis techniques for analyzing queueing networks is used. The model is shown to accurately predict measured system performance for two parallel program workloads that have different memory access characteristics. The results provide evidence that analytic queueing models can be extremely accurate in spite of simplifying assumptions required for model tractability. Model estimates are compared against detailed simulation of the bus to investigate in more detail the likely source of small model inaccuracies. The use of the analytical model for assessing system design tradeoffs is illustrated     

Impact of video scheduling on bandwidth allocation for multiplexed MPEG streams

We present efficient schemes for scheduling the delivery of variable-bit-rate MPEG-compressed video with stringent quality-of-service (QoS) requirements. Video scheduling is being used to improve bandwidth allocation at a video server that uses statistical multiplexing to aggregate video streams prior to transporting them over a network. A video stream is modeled using a traffic envelope that provides a deterministic time-varying bound on the bit rate. Because of the periodicity in which frame types in an MPEG stream are typically generated, a simple traffic envelope can be constructed using only five parameters. Using the traffic-envelope model, we show that video sources can be statistically multiplexed with an effective bandwidth that is often less than the source peak rate. Bandwidth gain is achieved without sacrificing the stringency of the requested QoS. The effective bandwidth depends on the arrangement of the multiplexed streams, which is a measure of the lag between the GOP periods of various streams. For homogeneous streams, we give an optimal scheduling scheme for video sources at a video-on-demand server that results in the minimum effective bandwidth. For heterogeneous sources, a sub-optimal scheduling scheme is given, which achieves acceptable bandwidth gain. Numerical examples based on traces of MPEG-coded movies are used to demonstrate the effectiveness of our schemes.     

Performance analysis of hierarchical cache-consistent multiprocessors

This paper investigates the potential performance of hierachical, cache-consistent multiprocessors. We have developed a mean-value queueing model that considers bus latency, shared memory latency and bus interference as the primary sources of performance degradation in the system. A key feature of the model is its choice of high-level input parameters that can be related to application program characteristics. Another important property of the model is that it is computationally efficient. Very large systems can be analyzed in a matter of seconds.

Results of the model show that system topology has an important effect on overall performance. We find optimal two-level, three-level and four-level topologies that distribute the bus traffic uniformly across all levels in the hierarchy. We provide processing power estimates for the optimal topologies, under a particular set of workload assumptions. For example, the optimal three-level topology supports 512 processors each with a peak processing rate of 4 MIPS, and provides an effective 1400 (1700) MIPS in processing power, if the buses operate at 20 (40) MHz. This result assumes 22% of the data references are to globally shared data and that the shared data is read on the average by a significant fraction of processors between write operations. Results of our study also indicate that for reasonably low cache miss rates (3% at level 0), and 20 MHz buses, the bus subnetwork saturates with processor speeds of 6–8 MIPS, at least for topologies of five or fewer levels. Finally, we present parametric results that indicate how performance is affected by one of the parameters that characterizes data sharing in the workload.     

公交优先无线传输系统设计

设计并制作出一款集MC13213控制、射频通信、信号处理等为一体的智能公交嵌入式系统。完全模拟了实际交通中公交进入十字路口、等待交通灯、离开十字路口等过程。系统在平均等待交通灯调度算法的基础上,改进并设计了一种公交优先算法。将在绿灯时间上给予公交车辆以优先权,解决了公交出行缓慢的问题。体现了路权的分配公平性。     

基于车辆载带中继的路边单元突发业务分组调度最优策略

高速公路车联网场景中, 路边单元(Roadside units, RSUs)可作为多种周边监测数据的汇入网关, 其业务具有突发特性, 且可通过移动车辆以“存储?载带?转发”方式传输到与骨干网络互联的RSU. 针对RSU间业务传输问题, 源RSU可根据实时业务到达率按需匹配资源, 以应对业务突发性对分组端到端时延的影响. 本文首先针对RSU突发业务传输过程建立突发业务到达模型、车辆到达模型和离散车速状态模型; 进而利用受限马尔科夫决策过程对系统状态转移过程进行分析, 并建立非线性平均端到端时延最小化问题; 最后通过分析最优解的形式得出最优分组调度策略具有门限结构. 仿真结果验证了RSU间业务传输过程中排队时延和传播时延之间存在折中, 且该分组调度策略能降低业务传输过程的平均端到端时延.     

Using processor-cache affinity information in shared-memorymultiprocessor scheduling

In a shared-memory multiprocessor system, it may be more efficient to schedule a task on one processor than on another if relevant data already reside in a particular processor's cache. The effects of this type of processor affinity are examined. It is observed that tasks continuously alternate between executing at a processor and releasing this processor due to I/O, synchronization, quantum expiration, or preemption. Queuing network models of different abstract scheduling policies are formulated, spanning the range from ignoring affinity to fixing tasks on processors. These models are solved via mean value analysis, where possible, and by simulation otherwise. An analytic cache model is developed and used in these scheduling models to include the effects of an initial burst of cache misses experienced by tasks when they return to a processor for execution. A mean-value technique is also developed and used in the scheduling models to include the effects of increased bus traffic due to these bursts of cache misses. Only a small amount of affinity information needs to be maintained for each task. The importance of having a policy that adapts its behavior to changes in system load is demonstrated