基于任务分配与调度的GSAT算法求解3-SAT问题

基于不同分配策略的云计算任务调度以及任务分配与调度的主要目的,提出了一种新的算法—求解3-SAT问题的基于任务分配与调度的GSAT算法。该算法将3-SAT问题中的每一个变量形成一个任务,在GSAT算法的基础上,引入任务分配与调度指导贪心搜索;同时,在保留原有贪心搜索的前提下,根据任务分配与调度的思想和3-SAT问题的特点,设计了两种新的策略—分配策略和调度策略共同完成整个贪心搜索过程。以标准的SATLAB库中变量个数从 20～250的3 700个不同规模的标准Uniform Random 3-SAT 问题对新的算法的性能进行了合理的测试,并与高效和普通性能改进的GSAT算法的结果作了比较,结果表明,该算法具有更高的成功率和更少的翻转次数。     

一种改进的小矩阵连乘算法

首先引入了矩阵的连乘优先因子,接着采用连乘优先因子最小的贪心选择策略,提出了最小连乘因子优先算法。它确定125的连乘次序不一定是最优次序,但在确定连乘次序方面比动态规划法花费的时间和空间少。最后通过实例对比测试,表明该算法在计算小矩阵连乘时,总体效率优于动态规划法。     

集合多覆盖问题的乘性权重更新分析

集合多覆盖问题的简单贪心算法的近似比是lnn＋1。本文提出简单贪心算法的一个变形，宽度优先贪心算法，并且证明其有近似比（lnn）／r＋lnlnn＋O（1），其中r是覆盖要求。这个结果比由随机取整方法得到的近似比O（（lnn）/r＋√（lnn）＋1为优。宽度优先贪心算法的设计可以归入Arora等最近提出的乘性权重更新方法的框架。关键词集合多覆盖，宽度优先贪心算法，乘性权重更新方法     

基于类TSP问题模型的操作系统磁盘移动臂驱动调度算法

将操作系统磁盘移动臂驱动调度问题抽象为类TSP问题,使用动态规划的方法对类TSP问题模型进行求解,得到某一时刻操作系统响应多个I／O请求最优序列的方法。由此提出基于贪心法的操作系统磁盘移动臂驱动调度的全局调度策略,即最短路径优先调度算法,并将最短路径优先调度算法与现有经典算法进行比较。     

常用作业调度算法的分析

作业管理、作业调度是操作系统的重要课题,该文讨论了先来先服务作业调度算法、短作业优先调度算法、最高响应比优先调度算法等常用作业调度算法的基本思想,并结合实例进行了分析和评价。     

一种基于汽车CPS的服务调度算法

驾驶者通过路边基础设施感知外部环境并根据经验作出反应是汽车信息物理融合系统的一个最基本的特点,研究汽车与路边基础设施信息交互对建设汽车信息物理融合系统具有重要意义。基于汽车与路边基础设施通信的场景,提出一种新的服务消息调度模型,设计了基于优先级的调度算法,采用贪心思想,优先调度效用值大的消息,将效用值小的消息进行插空调度,最后通过实验证明了本文算法的有效性。     

云环境下融合安全与可用性的DAG任务调度

在异构复杂的云环境中,任务调度时应保证资源的安全与可用性。为此,提出一种融合安全与可用性的DAG任务调度策略。改进主观逻辑信任模型,将计算出的资源信誉度作为调度的重要依据,对树云资源与DAG任务的可用性偏离度进行量化,给出调度函数并设计贪心调度算法( ISAG)。实验结果表明,在资源安全性和可用性较低的环境中,ISAG算法仍能满足用户需求,与表调度算法DLS和可用性优先调度算法Afsa相比,具有更高的任务执行成功率。     

虚拟计算环境中的多机群协同调度算法

基于虚拟计算环境的核心机理,提出由自主调度单元、域调度共同体、元调度执行体为核心的多机群协同系统框架.剖析多机群任务并发运行性能模型,设计了多机群协同调度算法框架,提出最大空闲节点优先、最小网络拥塞优先、最小异构因子优先与最小异构空闲节点优先4种启发式资源选择策略.实验验证了协同调度模型与算法在任务集完成时间与系统平均利用率的测度上的有效性.     

基于贪心算法和遗传算法的仓储车辆调度算法

针对仓储车辆调度问题提出一种基于贪心算法与遗传算法的调度算法。它主要利用遗传算法为框架筛选、进化出高效的调度方案,算法又融合了贪心算法对调度中的任务排序进行了快速优化。此融合使得遗传算法的编码简便,排除了不可行解的可能,从而使得算法性能大大提高。算法已经C++语言编程实现,实验分析证明:算法有效地提升了调度方案的效率。     

高实时性异构多核处理器任务调度算法

在异构多核处理器条件下,Min-Min算法调度性能较好但在系统实时响应方面存在不足。最小空闲时间优先调度算法(LSF)、最早截止时间优先调度算法(EDF)和最大价值优先调度算法(HVF)虽然在系统任务调度响应实时性方面表现优异,但却不适用于异构多核处理器环境。为此,提出一种高实时性任务调度算法HRSA。在Min-Min调度算法的基础上融合LSF,EDF,HVF算法的调度策略,将任务能耗、任务完成价值和任务响应比相结合,在实现异构多核处理器任务动态调度的同时缩短系统对高实时性任务的响应时间。实验结果表明,相对于EDF算法和Min-Min算法,HRSA算法消耗单位能量所带来的价值较高,对高实时性任务处理的响应时间较短。     

Translating Double Dispatch into Single Dispatch

Goals of flexibility and re-usability in typed object-oriented languages suggest the requirement of double dispatch, i.e., the mechanism of dynamically selecting a method not only according to the run-time type of the receiver (single dispatch), but also to the run-time type of the argument. However, many mainstream languages, such as, e.g., C++ and Java, do not provide it, resorting to only single dispatch. In this paper we present a general technique for adding double dispatch as a type-safe language feature, so yielding dynamic overloading and covariant specialization of methods, without extending basic semantics. To this aim we introduce a toy core language, extended to a full form of (non encapsulated) multi methods. Then we define a translation algorithm from multi methods to the core language, that implements double dispatch by using only standard mechanisms of static overloading and single dispatch. As a main feature, our translation preserves type safety, it uses neither RTTI nor type downcasts and does not introduce crucial overhead during method selection.     

Dynamic economic load dispatch using hybrid swarm intelligence based harmony search algorithm

This paper presents the hybrid harmony search algorithm with swarm intelligence (HHS) to solve the dynamic economic load dispatch problem. Harmony Search (HS) is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This work is an attempt to hybridize the HS algorithm with the powerful population based algorithm PSO for a better convergence of the proposed algorithm. The main aim of dynamic economic load dispatch problem is to find out the optimal generation schedule of the generators corresponding to the most economical operating point of the system over the considered timing horizon. The proposed algorithm also takes care of different constraints like power balance, ramp rate limits and generation limits by using penalty function method. Simulations were performed over various standard test systems with 5 units, 10 units and 30 units and a comparative study is carried out with other recently reported results. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.     

新颖的全局和声搜索算法在经济性调度中的应用

提出采用新颖的全局和声搜索算法来解决经济调度问题,并设计了一种新颖的处理系统约束的方法;介绍了经济调度问题数学模型、新颖的全局和声搜索算法实现过程及其应用方法。实验结果表明,采用新颖的全局和声搜索算法所获得的最优值要明显好于采用进化算法、粒子群算法所获得的最优值,新颖的全局和声搜索算法为解决经济性调度问题提供了一种新的解决方案。     

绝对时钟智能控制器的研制

介绍了一种日常参数智能控制器的研制及研制过程中的几个重要问题的解决方法。特别是用于城市照明及美化城市的彩灯的开、关时间智能控制方面，给出了依据当地绝对时间、经度、纬度进行昼夜时间计算的方法，使之在不接光电传感器情况下可跟踪季节的昼夜变化。控制系统采用８９Ｃ２０５１单片机，配有时钟日历芯片ＤＳ１２８８７，系统体积小、功能强、可靠性高。     

基于二维免疫的应急救援物资并行分配算法

现有应急救援物资分配研究大都局限于按照各发放点的优先级串行分配救援物资,难以适应复杂的大规模应急场景。为此,构建了面向多发放点的应急救援物资并行分配模型,并设计了基于二维二进制免疫和抗体修正的多发放点多救援物资并行分配算法。实验结果表明,该算法在大规模样本下较串行分配方法更加高效,能够从全局角度同时给出多个发放点的救援物资分配方案,为解决重大灾害中的复杂应急救援物资分配问题提供了一个有益的尝试。     

城市煤气供应系统优化调度

本文提出城市煤气供应系统优化调度的两级算法。首先，根据分解－协调原理，提出求解中压分配系统优化调度问题的一种算法；其次推导出低压分配系统优化调度问题的解析解，并提出相应算法。实例计算表明，其结果比较满意。     

电站多台机组经济运行算法研究

研究电厂多台机组经济运行的调度算法,开发 了电厂经济运行计算平台并将其加载在网控培训仿真机教员台上．首次将等微增率算法、浮 点数编码遗传算法和变尺度混沌优化算法等3种调度算法集中到一个计算平台上．给出了3种 调度算法的计算结果．采用3种调度方案的计算平台投入运行后将给电厂带来可观的经济效 益．     

Slot co-chartering and capacity deployment optimization of liner alliances in containerized maritime logistics industry

With the growing traffic of containerized shipping worldwide, container liners have seen increasing cooperation. Slot co-chartering has drawn wide attention as a way of cooperation within liner alliances. However, liners face the issue of finding proper measures to optimize alliance operations. In response to this, this paper comprehensively considers shipping capacity dispatch for containerized shipping companies within liner alliances. First, we explained the general rules of liner shipping dispatch and analyzed the interfering factors. Second, we created a liner shipping capacity dispatch model without consideration of slot co-chartering costs and a liner shipping capacity dispatch model with consideration of slot co-chartering costs and proposed a new column generation algorithm to solve both problems. Third, we tested our algorithm in a real case of a large Chinese containerized shipping company, which belongs to Ocean Alliance, and an optimal ship dispatch strategy on relevant routes and a decision on optimal slot chartering can be reached. Computational results indicate that the proposed column generation algorithm exhibits effective and efficient performance for large-scale slot co-chartering in liner shipping.     

Multiple dispatch in reflective runtime environment

Message dispatch in object-oriented programming (OOP) involves target method lookup in dispatch table/tree. Reflective environment builds dispatch data-structure at runtime as types can be added at runtime. Hence, algorithms for reflective environments require dynamic data structure for dispatch. In this paper, we propose a tree-based algorithm for multiple dispatch in reflective runtime environment. New classes can be added to the system at runtime. Proposed algorithm performs lookup in time proportional to $\log (n)$ times the polymorphic arguments, where n is number of classes in a system. Proposed algorithm uses type-safe approach for multimethod lookup resolving ambiguities. We compare performance of the proposed algorithm with the dispatch mechanism in commonly used virtual/reflexive systems, e.g., Java and Microsoft's Common Language Runtime (MS-CLR), in respect of efficiency and type-safety.     

Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling

To enable the immediate and efficient dispatch of relief to victims of disaster, this study proposes a greedy-search-based, multi-objective, genetic algorithm capable of regulating the distribution of available resources and automatically generating a variety of feasible emergency logistics schedules for decision-makers. The proposed algorithm dynamically adjusts distribution schedules from various supply points according to the requirements at demand points in order to minimize unsatisfied demand for resources, time to delivery, and transportation costs. The proposed algorithm was applied to the case of the Chi–Chi earthquake in Taiwan to verify its performance. Simulation results demonstrate that under conditions of a limited/unlimited number of available vehicles, the proposed algorithm outperforms the MOGA and standard greedy algorithm in ‘time to delivery’ by an average of 63.57% and 46.15%, respectively, based on 10,000 iterations.