基于2类决策和改进蚁群算法的多CCD调度

多CCD系统的调度要求同时兼顾调度质量与实时性。以无人值守变电站视频监视系统为研究对象,在考虑系统特性的基础上,以目标与CCD间距、节点载荷、优先级和模糊预测因子为指标,使用模糊决策动态调整预测区域半径,并建立基于2类决策的快速调度模型。对多目标调度的求解,研究了改进的最大最小蚁群算法,通过引入合适的收敛性判据和状态转移规则,避免了过多使用启发式算法造成的决策耗时,提高了决策的效率和算法的全局搜索能力。最后进行了系统仿真和真实实验,实验结果表明该方法可减少激活节点的数目,特别是对于较复杂的多CCD-多目标调度,能同时保证算法具有较好的实时性和求解性能,验证了模型的有效性。     

求解资源受限多项目调度的改进遗传规划算法

针对优先级规则调度不具备优化能力的缺陷，提出了一种应用于资源受限多项目调度的改进超启发式遗传规划算法以进化出更理想的优先级规则。通过分析现有优先级规则构建出适用多项目调度的归一化属性集和顶层判别编码方式，并结合NSGA-Ⅱ虚拟适应度分配方法对种群进行评估以实现多目标优化。设计了一种多样性种群更新方式，以避免传统遗传规划易陷入局部最优的缺陷和提高搜索能力。通过基于标准数据集PSPLIB所构造的算例和飞机总装装配线的生产实例验证了该方法的有效性和可行性。     

柔性作业车间动态调度方法研究

针对一类复杂工序的柔性作业车间的动态调度问题,提出了一种基于工序树的调度方案及算法。调度算法中采用多叉树形式的工序树,工序树是一种适用于作业车间调度的柔性工艺规划描述方法,工序树经过泛化和变形可以涵盖多种具体的工序样式。调度算法通过通信网络实时地获取加工车间中设备的工作状态,结合加工任务中所有产品的状态变迁,依据由加工任务的约束条件预先确定的优先调度规则,动态地生成加工任务作业进程表。算法实例的结果验证了调度方案及算法的有效性。     

一种基于多agent的柔性车间调度系统研究

针对柔性车间调度的特点,提出了一种分布式多agent柔性车间调度系统.系统由工件a-gent,生产单元agent和一个全局agent组成.生产单元agent根据三类agent相互协商得到总评价指数选择工件,工件agent根据特定规则选择加工设备进行加工.最后用Arena仿真软件建立模型,对柔性车间调度加权滞后和问题进行仿真实验,与传统的分派规则比较,结果显示基于多agent的柔性车间调度方法明显优于传统的分派规则.     

基于深度学习的资源投入问题算法

针对资源投入调度问题,提出了基于实时调度状态的调度优先级规则智能决策机制,构造了嵌合人工神经网络的双层迭代循环搜索算法.算法上层为启发式资源搜索框架,下层为基于实时调度状态的调度优先级规则智能决策算法.下层算法通过双隐层BP神经网络离线学习,获得调度状态与调度优先级规则的映射关系,并在实时调度过程中的每一阶段,根据当前调度数据,智能决策调度优先级规则,并指导作业调度进行.最后,通过标准算例库PSPLIB进行对比实验,验证了所设计算法的有效性.     

离散制造业作业调度中的优先判定方法研究

从宏观提升离散制造企业竞争力的角度,建立了一个用于生产调度的多目标决策的层次分析模型,提出一个基于层次分析法(AHP)的优先判定方法,实现了生产调度中调度目标的优先级确定,相应调度规则优先级的确定.解决了生产调度过程中调度目标定位不准,调度规则选定不合理的问题,为调度算法提供有效的支撑,使调度结果更加满足加工企业的实际生产状况,具有较强的理论研究价值与广泛的应用前景.     

启发式算法和遗传算法在生产调度中的应用

根据现代制造企业对生产调度的要求,提出了一种启发式算法和遗传算法相结合的生产调度系统结构。使用启发式规则为各工序分配机器,制定加工计划,调用遗传算法对加工计划进行排序,生成最终调度结果。通过将CLIPS推理机嵌入到系统中,实现了决策规则和程序体的分离,易于规则的修改和进一步扩展,系统更具有柔性。由启发式规则生成遗传算法的部分初始种群,提高了初始种群的质量。通过将任务分解,降低了问题求解的复杂度,并由实例验证了其可行性。     

基于知识的动态调度决策机制研究

针对基于知识的调度系统在实际应用中存在的知识源具有主观倾向性、决策依赖部分属性等缺陷，提出了一种新的基于知识的动态调度决策方法。在此基础上设计了调度决策系统。以合同网协议为协调机制，构建了基于多Agent的动态调度框架；由调度专家经验知识获取调度规则知识，并采用投票表决法解决规则知识的冲突，在实现知识融合的同时获得规则知识的可信度；对资源的调度历史记录进行学习，获取资源的条件属性可信度；利用粗糙集中定义的奈件属性重要度，计算调度规则知识中各条件属性重要度，并对其进行归一化处理，获取条件属性权值；提出了基于模糊Petri网的知识决策模型，以条件属性可信度为托肯、条件属性权值为输入强度、规则知识可信度为输出强度进行推理，得到决策属性可信度，形成决策结果。描述了动态调度系统的知识决策过程，完成了系统分析设计。     

启发式算法和遗传算法在生产调度中的应用

根据现代制造企业对生产调度的要求,提出了一种启发式算法和遗传算法相结合的生产调度系统结构.使用启发式规则为各工序分配机器,制定加工计划,调用遗传算法对加工计划进行排序,生成最终调度结果.通过将CLIPS推理机嵌入到系统中,实现了决策规则和程序体的分离,易于规则的修改和进一步扩展,系统更具有柔性.由启发式规则生成遗传算法的部分初始种群,提高了初始种群的质量.通过将任务分解,降低了问题求解的复杂度,并由实例验证了其可行性.     

混合流程企业的一种实用调度算法

以西北锆管有限责任公司的MIS系统(NWZ-MIS)的开发为背景,详细讨论了一种用于混合流程企业的实用调度算法。该算法的内容主要体现在以下几个方面:合并工艺文件中的相关工序,生成大工序工艺文件,使混合型加工从大工序的观点来看可近似为离散加工;以各工序的动态优先级和加工准备时间为参考完成静态调度:最后,讨论了算法中为增强调度柔性以解决该类企业加工调度中的某些特殊问题而采用的几种处理方法。     

Multiple-Objective Scheduling for the Hierarchical Control of Flexible Manufacturing Systems

This paper presents a hierarchical approach to scheduling flexible manufacturing systems (FMSs) that pursues multiple performance objectives and considers the process flexibility of incorporating alternative process plans and resources for the required operations. The scheduling problem is solved at two levels: the shop level and the manufacturing system level. The shop level controller employs a combined priority index developed in this research to rank shop production orders in meeting multiple scheduling objectives. To overcome dimensional complexity and keep a low level of work-in-process inventory, the shop controller first selects up to three production orders with the highest ranking as candidates and generates all possible release sequences for them, with or without multitasking. These sequences are conveyed to the manufacturing system controller, who then performs detailed scheduling of the machines in the FMS using a fixed priority heuristic for routing parts of multiple types while considering alternative process plans and resources for the operations. The FMS controller provides feedback to the shop controller with a set of suggested detailed schedules and projected order completion times. On receiving these results, the shop controller further evaluates each candidate schedule using a multiple-objective function and selects the best schedule for execution. This allows multiple performance objectives of an FMS to be achieved by the integrated hierarchical scheduling approach.     

Integrating Flexible Process Plans with Scheduling in Flexible Manufacturing Systems

This paper highlights the importance of integration between process planning and scheduling in flexible manufacturing systems (FMS). An effective integration increases the potential for enhanced system performance and enhanced decision making A framework that integrates flexible process plans with off-line (predictive) scheduling in FMS is presented. The flexibility in process planning, including process flexibility, sequence flexibility, and alternative machine tools, is discussed. The proposed framework consists of four integrated stages with the objective of reducing the completion time. The integrated stages include: 1. Machine tool selection. 2. Process plan selection. 3. Scheduling. 4. Re-scheduling modules. In addition, the paper proposes a new approach, namely the Dissimilarity Maximisation Method (DMM), for selecting the appropriate process plans for a part mix where parts have alternative process plans. The recursive structure of the framework provides a different approach, namely overlapping schedules, which considers a longer scheduling period as comprising several short scheduling periods. Knowing that neither the process plans nor the planned (predicted) schedules are truly followed on the shop floor, the related literature and the corresponding approaches are compared in order to envisage new approaches for closing the gap between process planning and scheduling.     

The Effects of Scheduling Rules and Routing Flexibility on the Performance of a Random Flexible Manufacturing System

The increased use of flexible manufacturing systems to efficiently provide customers with diversified products has created a significant set of operational challenges for managers. Many issues concerning procedures and policies for the day-to-day operation of these systems still are unresolved. Previous studies in this area have concentrated on various problems by isolating or simplifying the systems under study. The primary objective of this study is to extend previous research by examining the effects of scheduling rules and routing flexibility on the performance of a constrained, random flexible manufacturing system (FMS). Other experimental factors considered are shop load, shop configuration, and system breakdowns. Within the bounds of this experiment, the results indicate that, in the presence of total routing flexibility, the effects of shop load, system breakdowns, and scheduling rules are significantly dampened. In particular, when total routing flexibility exists, the choice of scheduling rules is not critical. We also show that the behavior of scheduling rules in a more constrained FMS environment (i.e., where system breakdowns occur and material handling capability is limited) is consistent with the findings of previous research conducted under less constrained environments. Finally, results indicate that the shop configuration factor has little or no impact on a system's flow-time performance.     

动态CAPP系统及其加工资源决策方法的研究

为提高工艺计划的可执行性，提出一种动态CAPP系统集成模型。在工艺计划产生过程中，考虑车间加工资源的状态以及能力，实现加工资源的合理选择，产生具有良好生产指导能力的工艺计划信息。在资源决策过程中，基于BP神经网络进行车间加工资源决策，利用相关算法计算对应于每一加工特征的加工资源的优先指标，按照优先指标排序。结果表明，利用该方法产生的工艺计划符合车间资源能力，满足车间生产计划的需求。     

Effectiveness of flexible routing control

Flexibility in part process representation and in highly adaptive routing algorithms are two major sources for improvement in the control of flexible manufacturing systems (FMSs). This article reports the investigation of the impact of these two kinds of flexibilities on the performance of the system. We argue that, when feasible, the choices of operations and sequencing of the part process plans should be deferred until detailed knowledge about the real-time factory state is available.To test our ideas, a flexible routing control simulation system (FRCS) was constructed and a programming language for modeling FMS part process plans, control strategies, and environments of the FMS was designed and implemented. In addition, a scheme for implementing flexible process routing called data flow dispatching rule (DFDR) was derived.The simulation results indicate that flexible processing can reduce mean flow time while increasing system throughput and machine utilization. We observed that this form of flexibility makes automatic load balancing of the machines possible. On the other hand, it also makes the control and scheduling process more complicated and calls for new control algorithms.     

基于制造网格的虚拟企业组织变更与制造资源调度问题研究

为提高虚拟企业的组织和运营效率，引入网格技术，基于制造网格构建面向应用的虚拟企业架构。在虚拟企业环境下，根据制造资源不同的调度阶段，分别建立基于外网格的虚拟企业制造系统和基于内网格的成员企业制造子系统；提出以制造资源特征匹配为核心的虚拟企业分布式调度策略和成员企业本地调度策略。针对特征匹配过程，建立制造资源特征集，对每个特征集制订相应的匹配准则，以保证特征匹配的可行性，进而完成调度过程。最后，通过定制型人工关节产品开发实例，阐述了基于制造网格的虚拟企业组织和制造资源调度过程。     

基于过程集成的闭环动态工艺规划系统

描述了一个在过程上实现工艺规划与车间规划集成的闭环动态工艺规划系统,建立了实用化CAPP系统的新模型,丰富了动态CAPP的概念。它能根据车间环境的状态,充分利用制造工艺和车间环境的柔性产生优化的工艺方案。系统在车间环境约束下采用专家系统技术进行非线性工艺规划,产生可选工艺路线和工序可选设备。在一个由工艺路线选择、设备动态优化选择和车间优化规划构成的闭环系统中,以高生产效率为目标,根据推广的关键路线分析的结果和一系列启发式知识动态地选择工艺路线和设备,最后获得有较高实践意义的结果。     

Integration of process planning and scheduling in a job shop environment

Today’s manufacturing systems are striving for an integrated manufacturing environment. To achieve truly computer-integrated manufacturing systems (CIMS), the integration of process planning and production scheduling is essential. This paper proposes a framework for integration of process planning with production scheduling in a job shop environment for axisymmetric components. Based on the design specifications of incoming parts, feasible process plans are generated taking into account the real time shop floor status and availability of machine tools. The scheduling strategy prioritizes the machine tools based on cost considerations.     

基于多智能体结构的车间调度方法

车间调度问题是一个复杂的 NP问题 ,车间调度系统需要具有相当的柔性机制。本文提出了一种基于多智能体结构的车间层动态调度方法。系统中有三种代理 ,车间代理、资源代理和任务代理协同并行工作。车间代理负责各个任务代理之间的协调 ,任务代理安排任务的调度路径 ,资源代理安排车间中的具体制造资源。车间代理能够动态调整调度规则 ,解决任务代理之间的资源分配冲突。任务代理采用招标投标机制选择最佳资源代理。资源代理能够提出并实时调整局部调度方案。本文实现了一个基于多智能体结构的车间调度原型系统。     

一种改进的遗传算法在车间调度中的应用

研究现代生产先进制造车间调度问题 ,对于发挥先进制造车间的高效性和灵活性具有十分重要的意义。生产过程的计划调度问题 ,是实现制造系统运筹技术、管理技术与优化技术的核心。因此 ,优化调度算法的性能直接影响到FMS的生产效率和应变能力。本文在传统的遗传算法的基础上 ,对车间调度算法进行了深入的研究。基于机床负荷平衡的思想 ,提出了面向先进制造车间的平衡遗传算法 ,并与传统的遗传调度算法进行了对比。实验表明 ,该调度方法具有较高的可行性、有效性和稳定性。保证了各个机床的负荷平衡 ,满足了交付期的要求