基于CSCW的选煤厂生产调度管理系统

针对选煤厂生产调度的自身特点,以大屯选煤厂生产调度的实际情况为背景,介绍了基于CSCW的选煤生产调度管理系统,并对此系统的安全性和异构为数据库的访问做了阐述。     

武钢二炼钢厂炉机匹配系统算法研究

武钢集团第二炼钢厂的炉机匹配系统可简化为两道工序的车间作业排程问题。其问题的关键在于合理调配3台转炉的工作时段以满足4台铸机的不间断运转。本文提出了一种快速有效的算法——压缩-扩张算法，为整个系统的最后实现，提供了最关键的支持。     

Applications of optimal mathematic-physical models in metallurgical manufacture scheduling system at Baosteel

The transfer of mass flow between ironmaking and steelmaking process at Baoshan Iron and Steel Co. Ltd. has been analyzed. The mathematic-physical models of transport scheduling for hot metal manufacturing have been researched combined with the practical problem in the metallurgical manufacture procedure. Taking into account these models, the scheduling software has been designed, programmed and tested on-line. The new automation system of production scheduling has been implemented successfully at Baosteel, which produces a great economic benefit.     

Odyssey: a high‐performance clustered video server

Video servers are essential in video‐on‐demand and other multimedia applications. In this paper, we present our high‐performance clustered CBR video server, Odyssey. Odyssey is a server connecting PCs with switched Ethernet. It provides efficient support for normal play and interactive browsing functions such as fast‐forward and fast‐backward. We designed a set of algorithms for scheduling, synchronization and admission control, which results in a high utilization of resources. Odyssey is able to deliver a large number of video streams. Copyright © 2003 John Wiley & Sons, Ltd.     

基于优先数的智能生产调度系统

生产调度是企业生产中的关键环节,也是实施CIMS的重点。该文介绍了一种基于优先数的动态、多目标优化生产调度方法,并构造了一个基于优先数的智能生产调度系统。系统通过Agent对生产调度问题中的各个目标优化,给出不同目标的指标值,同时给出企业在不同时候对不同目标的偏好值,计算各个生产任务的优先数,根据任务的优先数安排生产。     

RSView32组态软件在火电厂生产调度监控系统中的应用

主要论述了RSView32组态软件，在火电厂生产调度监控系统中的应用，并介绍了使用高新技术网络采集控制器NETRTU。其配置简捷、高速和可靠，将代表着自动化硬件新的发展趋势，与RSView32组态软件配合使用真可谓绵上添花。     

Striping and Scheduling for Large Scale Multimedia Servers

When designing a multimedia server, several things must be decided: which scheduling scheme to adopt, how to allocate multimedia objects on storage devices, and the round length with which the streams will be serviced. Several problems in the designing of large-scale multimedia servers are addressed, with the following contributions: (1) a striping scheme is proposed that minimizes the number of seeks and hence maximizes the performance; (2) a simple and efficient mechanism is presented to find the optimal striping unit size as well as the optimal round length, which exploits both the characteristics of VBR streams and the situation of resources in the system; and (3) the characteristics and resource requirements of several scheduling schemes are investigated in order to obtain a clear indication as to which scheme shows the best performance in realtime multimedia servicing. Based on our analysis and experimental results, the CSCAN scheme outperforms the other schemes. It is believed that the results ar     

求解网络广告资源优化模型的改进微粒群算法

针对网络广告的特点，提出一个最大化广告效果函数的广告资源分配模型．在Langheinrich线性模型的基础上，加入分散广告显示的二次惩罚项，使所得到的最优解更能发挥网络广告的作用，结合微粒群(PSO)算法和模型的特点，设计出能有效处理约束的改进PSO算法，数值仿真证明了算法的有效性。     

改进计算能量函数下作业车间调度的混沌神经网络方法

神经网络是求解作业车间调度问题的一种有效方法,本文研究可以获得全局最优或近似全局最优的可行解的作业车问调度神经网络方法.给出包括作业车间调度所有约束条件的新的计算能量函数表达式,并把混沌动力学应用于离散Hopfield神经网络作业车间调度中,提出一种改进的暂态混沌离散神经网络作业车间调度方法.仿真结果表明,该方法不仅具有全局搜索能力,而且收敛速度较快,重要的是能够保证神经网络的稳态输出为全局最优或近似全局最优的可行的作业车间调度方案.     

Coordinated scheduling of production and delivery from multiple plants

This paper deals with the scheduling of orders and vehicle assignment for production and distribution planning in a scenario of no-wait, immediate delivery to the customer site. We first describe the problem and then present an integer programming model that maximizes the weighted value of the orders served. We consider a special case of the problem which can be solved in polinomial time by a minimum cost flow algorithm. Based on this approach we develop a heuristic procedure for the general case. Comparisons with an exact graph-based method attest that our heuristic produces good-quality solutions in short running times.