虚拟计算环境实验床平台的设计与实现

虚拟计算环境的提出是为了克服互联网资源的"成长性、自治性和多样性"等自然特性与通过全局集中控制达到资源有效共享和综合利用的矛盾.基于虚拟计算环境的体系结构和核心概念,部署了一个真正开放性、分布式的大规模网络环境,在其上设计与实现了一个三层实验床平台系统,包括资源组织、监测、调度、安全等子系统.在平台上进行了网络信息获取实验,验证了该平台设计的科学性与合理性,从实现角度给了虚拟计算环境一个可行的参考.     

不确定环境下的单机成套订单鲁棒计划

讨论了不确定环境下订单数量可变的单机成套计划的优化问题,利用对偶变换给出了该问题的鲁棒整数规划模型,并设计了相应的遗传算法。算法对约束条件难点的处理采用了四种不同的方法即死亡惩罚、罚函数法、修补方法和解码方法,以检验算法的性能。最后进行了数值仿真实验,以比较不同算法的有效性。     

Domain–Specific High–Level Modeling and Synthesis for ATM Switch Prototyping

ATM switch, the core technology of an ATM networking system, is one of the major products in Fujitsu telecommunication business. However, current gate–level design methodology can no longer satisfy its stringent time–to–market requirement. It becomes necessary to exploit high–level methodology to specify and synthesize the design at an abstraction level higher than logic gates. This paper presents our prototyping experience on domain–specific high–level modeling and synthesis for Fujitsu ATM switch design. We propose a high–level design methodology using VHDL, where ATM switch architectural features are considered during behavior modeling, and a high–level synthesis compiler, MEBS, is prototyped to synthesize the behavior model down to a gate–level implementation. Since the specific ATM switch architecture is incorporated into both modeling and synthesis phases, a high–quality design is efficiently derived. The synthesis results shows that given the design constraints, the proposed high–level design methodology can produce a gate–level implementation by MEBS with about 15 percent area reduction in shorter design cycle when compared with manual design.     

基于需求响应的虚拟电厂多时间尺度优化调度

随着我国不断加快新型电力系统建设,风电、光伏等越来越多的分布式资源大规模并网,但其随机性、波动性及分散性的特点给电力系统带来了多重不确定性。提出了一种考虑价格型需求响应的虚拟电厂多时间尺度优化调度方法,在日内调度模型中引入用户价格型需求响应,对用户负荷进行精准调控;采用基于蒙特卡罗与曼哈顿概率距离的场景生成与削减法处理风光出力、电价不确定性,减少日前日内出力偏差,再结合日前调度构成了多时间尺度优化调度模型,并采用滚动优化得到日内优化调度结果。以湖南某小型虚拟电厂系统进行算例仿真,结果表明,所提多时间尺度优化调度策略能够精确预测风光出力及用户负荷,在有效抑制功率波动的同时保证了系统的经济性。     

高风电渗透率下考虑需求侧管理策略的智能微电网调度方法

提出了一种高风电渗透率下考虑需求侧管理策略的智能微电网调度方法.首先,考虑经济、环境成本指标、清洁能源就地消纳量以及可中断负荷和可转移负荷策略,建立了多目标优化调度模型.然后,引入ε约束法生成Pareto前沿解集,利用归一化方法求出最优折衷解.最后,基于24节点配电系统对所提方法进行分析验证.算例结果表明:建立的多目标...     

清江梯级水电厂集中控制优化调度

介绍了清江梯级水电厂开展集中控制优化调度过程中产生的效益、面临的问题,及对今后工作的建议及展望。     

一体化生产管理系统炼钢计划子系统设计

概述了炼钢—连铸—热轧一体化生产管理系统的设计方案,采用软件工程方法开发炼钢计划与实绩管理子系统,简要介绍了子系统功能构成及动态调整设计．实验室模拟运行效果良好．     

基于加气站槽车调度的模型建立与算法研究

通过对CNG的发展形势介绍,深入到要研究的具体问题——槽车调度,槽车调度就是加气站母站向子站调度发送槽车。匈牙利算法是用到线性规划上解决最优化最优解的问题。考虑到槽车调度优化的问题的特殊性,因此在匈牙利算法的思想基础上,提出了最大差值法。此方法能更高效率地运算出最优解。     

Fuzzy uncertainty modelling for project planning: application to helicopter maintenance

Maintenance is an activity of growing interest, especially for critical systems. In particular, aircraft maintenance costs are becoming an important issue in the aeronautical industry. Managing an aircraft maintenance centre is a complex activity. One of the difficulties comes from the numerous uncertainties that affect the activity and disturb the plans in the short and medium term. Based on a helicopter maintenance planning and scheduling problem, we study in this paper the integration of uncertainties into tactical and operational multi-resource, multi-project planning (respectively Rough Cut Capacity Planning and the Resource Constraint Project Scheduling Problem). Our main contributions are in modelling the periodic workload on a tactical level considering uncertainties in macro-task work content, and modelling the continuous workload on the operational level considering uncertainties in task duration. We model uncertainties using a fuzzy/possibilistic approach instead of a stochastic approach since very limited data are available. We refer to the problems as the Fuzzy Rough Cut Capacity Problem (FRCCP) and the Fuzzy Resource Constraint Project Scheduling Problem (RCPSP). We apply our models to helicopter maintenance activity within the frame of the Helimaintenance project, an industrial project approved by the French Aerospace Valley cluster that aims at building a centre for civil helicopter maintenance.     

Day of the week lost time occupational injury trends in the US by gender and industry and their implications for work scheduling

While there is a growing body of research on the impact of work schedules on the risk of occupational injuries, there has been little investigation into the impact that the day of the week might have. The present research was completed to explore day of the week trends, reasons for such trends and the corresponding implications for work scheduling. Data for the number of injuries and illnesses involving days away from work (lost time; LT) in 2004 were provided by the US Bureau of Labor Statistics Office of Safety and Health Statistics. Data from the American Time Use Survey database were used to estimate work hours in 2004. From these two data sources, the rate of LT injuries and illnesses (per 200 000 work hours) by day of the week, industry sector and gender were estimated. The analysis revealed clear differences by day of the week, gender and major industry sector. Sundays had the highest rate overall – nearly 37% higher than the average of the remaining days, Monday to Saturday. Mondays had the next highest rate followed closely by Saturdays. This pattern was not the same for males and females. For males, Mondays had the highest LT rate (27% higher than the average of all other days) with all remaining days having essentially the same rate. For females, Sundays and Saturdays had much higher LT rates – 122% and 60% higher, respectively, than the average weekday rate. There were also differences by industry and differences between genders by industry. The present analysis suggests that several factors may be contributing to the weekend and Monday trends observed. Lower-tenured (and younger) workers on the weekends, lower female management/supervision and second jobs on the weekend seem to be contributors to the high Saturday and Sunday LT rates. Differences in day of the week employment by industry did not account for the trends observed. Fraud and overtime also could not be confirmed as contributing to these trends. Monday trends were more complex to explain, with possible explanations including non-work-related weekend injuries being reported on Mondays, soft-tissue symptoms becoming more noticeable on Mondays, greater Monday morning flexion risk and reduced supervision in the construction industry on Mondays. Interpretation of these trends and the implications for work scheduling are discussed.