计算机辅助车间实时调度系统

本系统是汉江机床厂管理信息系统中的一个子系统，其开发工具采用ＦｏｘｐｒｏｆｏｒＷｉｎｄｏｗｓ关系数据库，它运用启发式方法编排车间零件加工计划，对编制短期加工计划具有较强的实时性，系统的运用对于提高车间一级的管理水平具有现实意义。     

柔性作业车间生产计划与调度集成优化求解策略

针对柔性作业车间(Flexible job-shop, FJS)生产计划(Production planning, PP)与调度紧密衔接的特点, 建立了生产计划与调度集成优化模型. 模型综合考虑了安全库存、需求损失及工件加工路线柔性等方面因素. 提出了一种基于拉格朗日松弛(Lagrangian relaxation, LR)的分解算法, 将原问题分解为计划子问题与调度子问题. 针对松弛的生产计划子问题, 提出一种新的费用结构, 以保证生产计划决策与实际情况相符, 并设计了一种变量固定—松弛策略与滚动时域组合算法进行求解. 对于调度子问题中的加工路线柔性问题, 提出了一种新的机器选择策略. 通过数值实验验证了模型与算法的有效性.     

AJ—System生产作业调度系统的柔性设计及其实现

从柔性设计的角度出发,围绕一个具体的机械加工车间,详细阐述了AJ-System系统的柔性设计方法,并简单介绍了系统的框架及其应用。这种柔性设计方法也为其它相关系统的开发提供借鉴。     

柔性自动化车间的随机生产设计与控制

研究了柔性自动化车间（ＦＡＷ）的随机生产计划与控制问题，提出了一种随机生产计划新方法。文中首先建立ＦＡＷ随机生产计划与控制的数学模型，然后推导求解该问题的算法，编制相应软件，进行算例研究，研究表明，本算法能够有效地将不确定性环境中的ＦＡＷ产品需求计划最优分解成由ＦＡＷ中种ＦＭＳＡ执行的短期随机计划。     

基于ODBC的车间生产调度系统的研究与开发

对某车间生产调度问题进行研究并开发出基于ODBC接口的调度系统。通过对寻优空间的收缩,使调度问题的寻优空间最小化,大大提高寻优的速度,从而得到可应用于实际生产的调度系统。     

基于多Agent协商的柔性车间调度系统

针对柔性作业车间调度的特点,提出了一种基于多agent协商的柔性作业车间调度系统。系统由工件agent,机器agent和工序agent组成。Agent之间通过相互发送消息和响应消息进行交互,并且通过消息相应函数按照各agent局部的信息、同时兼顾系统的性能进行决策。工件agent通过招标的方式,选择合适的机器完成加工任务,机器agent通过竞争来获得工件的加工权。最后用Java语言在Eclipse平台上进行程序设计,对柔性作业车间调度的平均滞后问题进行仿真实验,并与传统的分派规则比较,结果显示所提方法的优越性。     

柔性作业车间调度分析及其启发式算法

针对多目标柔性作业车间调度问题,基于甘特图和搭积木经验进行了分析,提出了一种组合优先规则和基于此优先规则的启发式算法。组合优先规则面向完工时间、关键机床负荷和总负荷三个指标,改变规则中各数据项的比例可调整三个指标所占的比例。算法采用随机方式调整三个指标的比例,并微调最优解对应的比例,能随机产生多个高质量调度解。对比测试表明,算法求解质量更高,运行速度快,稳定,可直接用于在其他调度算法中产生初始解,或者用于动态调度。     

柔性制造单元的智能调度系统

本文基于递阶控制原理提出了柔性制造单元的一种新的计划与调度方法,并综合采用了理论分析、专家系统技术和仿真技术,建立了一个智能调度系统原型.另外,在制造单元调度问题的描述上采用了状态方程形式,从系统的观点来研究调度问题.并在此基础上建立了仿真模块,对单元的加工过程进行了仿真实验.     

柔性作业车间调度的多Agent协商策略

柔性作业车间调度问题是经典作业车间调度问题的扩展。为此,提出一种新的基于招投标的多Agent协商调度策略,并研究各Agent协商时的价格函数。系统主要由工件Agent和机器Agent组成,工件Agent通过招投标的方式,选择合适的机器完成加工任务,机器Agent按照市场机制通过自由竞争获得工件的加工权,根据基于规则的调度策略处理工件。用Java设计仿真实验程序,并通过实验验证所提价格协商函数的有效性。     

一种面向柔性生产的动态调度模型*

为解决柔性生产中两个生产单元与多作业对象的优化调度问题,提出一种基于能力平衡的动态调度模型。将生产单元模型化为一种容器,把生产能力视为容积,并划分为设定能力和机动能力。通过建立两单元的机动能力连通模型,根据流体力学原理提出了一组动态调度规则,并开发了可用于现场调度的高效的启发式优化算法。在滚装运输企业进行的案例研究表明,该模型及其算法在实际生产运作中具有切实的可行性和有效性。     

An application of a real-time scheduling system for turbulent manufacturing environments

Classical scheduling approaches are not effective in real plants since they assume highly unrealistic assumptions that are seldom found in practice. These assumptions mainly deal with the consideration of the manufacturing environment as static. But in most real manufacturing installations some unexpected events take place. Ignoring these events may lead to schedules of unacceptable performance. Moreover, a quick reaction to changes is necessary, taking into account the significant amount of indirect costs involved in the derived interruptions. Reactivity and flexibility have to become key requirements at high control levels since they can contribute to shorten throughput times, improve equipment utilisation rates and service to customers. There is a need to extend classical scheduling models, so that they are able to better represent the factory. Genetic algorithms stand for one of the most promising alternative techniques to the classical ones. They show non-linearity, domain independence, robustness and flexibility. In this article, an evolutionary genetic algorithm has been used for sequencing job-shop problems in a real-time environment. Untoward events such as lack of materials or tools, change in production orders or unavailability of machines have been represented in the model and a solution using genetic algorithms has been designed and implemented. In the context of a European project belonging to the Competitive and Sustainable Growth programme, a prototype of a dynamic scheduler using genetic algorithms is described and some conclusions are drawn regarding the feasibility and quality of the solution.     

组合规则启发式算法在模具加工作业调度中的应用研究

由于现行的优化算法在解决模具车间调度问题上存在局限性,目前大部分模具车间由人工编制车间作业计划,导致生产效率较低、物料供应不能同步化等问题.为此,介绍了采用基于组合规则的启发式算法,选择加工时间最短和最小等待时间等规则,解决了现行的优化调度算法在车间调度问题中所遇到的难点.经实例验证获得了较为理想的结果.     

改进生物地理学算法求解柔性作业调度问题

针对柔性作业车间调度问题的特点,提出了一种基于改进生物地理学优化算法的求解方案。该方案采用基于工序和基于机器相结合的编码机制,在初始种群中引入启发式算法生成的优良个体,并在标准生物地理学算法基础上对迁移和变异操作进行了改进,采用符合该调度问题的迁移率模型和自适应变异机制,克服了传统算法易于早熟或收敛慢的缺点。通过仿真验证了该算法的可行性和有效性。     

A flexible real-time scheduling abstraction: design and implementation

An evolution is happening in the way that operating systems support the real-time requirements of their applications. The need to run real-time applications such as multimedia in the same environment as complex non-real-time servers and applications has motivated much interest in restructuring existing operating systems. Many issues related to thread scheduling and synchronization have been investigated. However, little consideration has been given to the flexibility and modularity required in the support of application-level scheduling needs, although it is well known that application requirements are diverse. In this paper, we describe a real-time scheduling abstraction which provides modularity and flexibility to the scheduling support of operating systems. Our design has been implemented using the Mach 3.0 kernel and a locally developed multiprocessor kernel (the r-kernel) as development platforms. © 1997 John Wiley & Sons, Ltd.     

A research survey: review of flexible job shop scheduling techniques

In the last 25 years, extensive research has been carried out addressing the flexible job shop scheduling (JSS) problem. A variety of techniques ranging from exact methods to hybrid techniques have been used in this research. The paper aims at presenting the development of flexible JSS and a consolidated survey of various techniques that have been employed since 1990 for problem resolution. The paper comprises evaluation of publications and research methods used in various research papers. Finally, conclusions are drawn based on performed survey results.     

基于PB的FPSS系统的设计及其开发

如何在多品种小批量的生产环境下快速经济地得出生产作业调度方案是目前研究的热点。文章围绕一个机械加工公司展开,利用启发式算法来解决生产排序调度问题,并讨论了调度规则库的构建。FPSS系统运行表明:能快速得出生产作业排序调度方案,能根据内外环境的变化快速做出有效的资源调整。     

Minimizing cycle time and group scheduling, using Petri nets a study of heuristic methods

The objective of this paper is a study of minimizing the maximum completion time min F _max, or cycle time of the last job of a given family of jobs using flow shop heuristic scheduling techniques. Three methods are presented: minimize idle time (MIT); Campbell, Dudek and Smith (CDS); and Palmer. An example problem with ten jobs and five machines is used to compare results of these methods. A deterministic t-timed colored Petri net model has been developed for scheduling problem. An execution of the deterministic timed Petri net allows to compute performance measures by applying graph traversing algorithms starting from initial global state and going into a desirable final state(s) of the production system. The objective of the job scheduling policy is minimizing the cycle time of the last job scheduled in the pipeline of a given family of jobs. Three heuristic scheduling methods have been implemented. First, a sub-optimal sequence of jobs to be scheduled is generated. Second, a Petri net-based simulator with graphical user interface to monitor execution of the sequence of tasks on machines is dynamically designed. A deterministic t-timed colored Petri net model has been developed and implemented for flexible manufacturing systems (FMS). An execution of the deterministic timed Petri net into a reachability graph allows to compute performance measures by applying graph traversing algorithms starting from initial global state to a desirable final state(s) of the production system.     

猫群优化算法求解柔性作业车间调度问题

根据柔性作业车间的生产特点,对基本猫群优化算法进行设计和改进,提出了一种改进型猫群优化算法（Improved Cat Swarm Optimization,ICSO）,用于优化车间内工件的最大完工时间。算法给出了两段式个体位置编码方式和基于启发式算法的种群初始化策略;采用自适应行为模式选择方法,使其能够有效协调算法全局和局部搜索;提出了基于多样化搜寻算子的搜寻模式,增强算法的全局搜索能力;提出了基于莱维飞行的跟踪模式,增强算法的局部搜索能力。此外,算法中还引入了跳跃机制,使算法性能能够得到进一步的改善。实验数据表明ICSO算法在求解FJSP问题方面具有一定的有效性。