多机器人存取系统动态调度方法

针对多机器人存取系统实时性要求高,动态事件发生时易偏离调度计划的难题,提出一种动态调度方法。对系统内发生的动态事件进行分析,确定不同动态事件造成的后果和对调度的影响。建立以完成时间最小为目标的动态调度模型。提出动态调度方法实现系统内实时订单到达情况下的预调度和动态事件发生后的重调度。根据动态事件的不同影响,确立动态事件发生时的重调度规则。通过实例证实,相比现有调度方法,所提出的动态调度方法能够及时响应紧急订单到达和机器人故障等动态事件的发生,获得完成时间更小且路径长度更短的调度方案,选择在故障时间后对受影响机器人进行重调度对重调度结果的影响更小。     

基于Memetic算法的车间动态调度策略研究

针对车间动态调度问题的求解,提出了一种基于Memetic算法的车间动态调度策略。该策略结合滚动窗口机制,并采用基于周期和事件的混合驱动策略,运用Memetic算法对每个滚动窗口工件集进行重调度。该算法采用顺序交叉算子和基于邻域搜索的新型变异算子,在交叉和变异后均采用改进的模拟退火策略进行局部搜索。通过对改进后的基准实例进行实验,验证了该策略的有效性。     

动态上下料路径下柔性产品族生产调度研究

针对汽车零部件柔性产品族制造单元考虑工序间动态上下料路径与时间的生产调度求解问题,文中提出一种用于动态上下料路径柔性作业调度问题优化的自适应离散差分进化算法。通过自适应缩放参数实现收敛速度提升,构建基于矩阵映射的离散编码规则实现变异操作离散化及基于机器人实际运动路径的动态调度解码。通过对某平台化车型架构的转向器壳体加工单元实例分析并验证了算法有效性及优越性。     

基于Memetic算法的车间动态调度策略研究

针对车间动态调度问题的求解,提出了一种基于Memetic算法的车间动态调度策略。该策略结合滚动窗口机制,并采用基于周期和事件的混合驱动策略,运用Memetic算法对每个滚动窗口工件集进行重调度。该算法采用顺序交叉算子和基于邻域搜索的新型变异算子,在交叉和变异后均采用改进的模拟退火策略进行局部搜索。通过对改进后的基准实例进行实验,验证了该策略的有效性。
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基于Agent的智能制造系统实时动态调度机制研究

近年来随着制造企业生产过程中不确定因素增加,动态调度问题变得愈发复杂。在多Agent制造系统基础上提出了一种基于事件触发的制造系统实时动态调度机制,建立了相应的架构模型,并从调度方法、多Agent协调控制,以及调度控制算法等方面对该机制进行了详细说明。该机制可以根据系统运行状态实现车间层的实时控制和动态调度。最终通过实验表明该方法有效减少设备故障等扰动因素对系统运行的影响。     

基于滚动调度的模具热处理车间负荷控制算法

针对模具热处理车间生产难以有效控制这一实际问题,提出一种基于负荷控制理论的生产计划与控制方法.建立模具制造车间三层负荷控制模型,并针对热处理车间,分析其负荷控制的关键问题,给出一种考虑负荷动态均衡性的热处理任务转序决策方法;构建以交货表现和设备利用率为双目标的优化调度模型;应用离散事件仿真原理和折衷规划理论,建立一类基于周期和事件驱动的混合滚动调度求解算法,并分析该算法的时间复杂度;以所提算法为基础,开发热处理车间生产计划系统,通过该系统计算得到多组目标函数权重下的算法调度结果,进一步分析不同权重对算法的影响,并同时与其他几类算法的调度结果进行对比分析,说明所提算法的实用性和有效性.     

基于改进粒子群优化算法的多目标铜卷加工生产调度研究

针对多目标铜卷加工生产调度问题,提出一种自适应的改进粒子群优化算法。该算法采用基于个体拥挤距离排序的外部种群保留策略以避免陷入局部极值,基于个体拥挤距离概率更新全局极值以及基于支配关系更新个体极值,同时采用基于非支配解和单点交叉的内部种群规模自适应调整策略以及自适应动态惯性权重来保持种群的多样性。通过应用实例验证了该方法求解多目标铜卷加工生产调度问题的有效性。     

面向数字孪生的船用柴油机装配车间生产调度

在船用柴油机装配过程中,普遍存在动态扰动事件频发、生产状态监控不足等缺陷,导致生产过程偏离调度计划且无法对扰动事件进行快速响应。为解决调度计划偏差和快速响应这两个难题,将数字孪生技术应用于船用柴油机装配车间生产调度过程中,通过物理装配车间与虚拟装配车间的实时交互快速响应扰动事件并减少调度计划偏差。构建了一种基于数字孪生的船用柴油机装配车间生产调度框架,并对装配调度问题进行描述与建模。详细阐述了动态调度流程并提出了一种基于pareto支配规则的多目标离散蚁狮优化算法来优化最大完工时间和装配班组负荷这两个调度目标,保证了调度方案的实时性和准确性。最后,通过在某型号柴油机装配车间部署运行,验证了此种调度模式的有效性。     

双资源约束作业车间动态调度研究

针对双资源约束作业车间动态调度优化问题的求解特点,基于局部时窗调度思想构造包含动态扰动分析、动态扰动评估以及动态调度方法在内的三层动态调度系统,并结合最小化调度方案修订的动态调度实际需求,设计基于染色体还原机制与局部工序的分阶段调度优化的混合动态调度算法,最后通过仿真实验验证了基于局部时窗调度思想的动态调度方法有效降低随机扰动影响的良好应用效果。     

多目标柔性作业车间稳健性动态调度研究

研究了以调度稳定性和鲁棒性为优化目标的柔性作业车间动态调度问题。建立了多目标柔性作业车间动态调度问题模型;针对动态事件特点,采用工件到达发生器和机器故障预维护发生器模拟动态事件,提出了基于周期与事件驱动的混合重调度策略,该策略在每个重调度点对工件进行完全重调度或右移重调度;为克服传统差分算法早熟的缺点,设计了一种改进的多目标差分进化算法求解该调度问题;实例验证了提出策略和算法的有效性。     

Rule- and PSO algorithm-based dynamic spatial rescheduling method for hull curved block construction

Due to no effective rescheduling method in hull curved block construction planning, existing scheduling planning can’t be applied in practical production effectively. Two-dimensional layout and dynamic attributes of block construction planning are considered to develop a spatial rescheduling method, which is based on the spatial points searching rule and the particle swarm optimization(PSO) algorithm. A dynamic spatial rescheduling method is proposed to solve the manufacturing problem of rush-order blocks. Through spatial rescheduling, the rescheduling start time, the current processing information set and rescheduling blocks set can be obtained automatically. By using and updating the data of these sets, the rescheduling method combines the PSO algorithm with the spatial points searching rule to determine the rescheduling start time and layout of the blocks. Three types of dynamic events, including rush-order block delay, existing block delay and existing block position changes, are used to address problems with different function goals by setting different function weights. Finally, simulations based on three types of rush-order block events are performed to validate this method, including single rush-order block, multi rush-order blocks at the same time and multi rush-order blocks at different times. The simulation results demonstrate that this method can solve the rush-order block problems in hull block construction and reduce the interference to the existing manufacturing schedule. The proposed research provides a new rescheduling method and helps instruct scheduler to make production planning in hull block construction.     

基于自适应蚁群算法的动态作业车间调度问题的求解方法

针对目前大多数作业车间调度算法都是静态调度,而实际工业生产中调度任务都是动态变化的问题,提出了一种求解动态作业车间调度问题的自适应蚁群算法.算法采用事件驱动调度策略,当调度任务发生变化时根据上次调度结果重新调度,并且对每次调度采用自适应蚁群算法优化调度方案.最后,通过实例仿真验证了算法的有效性.仿真结果表明,该算法自适应性表现在算法针对"搜索结果是否陷入局部收敛"分别对各路径上的信息素进行了自适应调整,有助于算法快速跳出局部收敛,继续向全局最优解进行搜索.     

一种多品种变批量柔性作业车间调度方法

文中针对多品种变批量柔性生产车间交付周期长、设备利用不均衡、生产效率低的问题,提出了一种基于遗传算法的多品种变批量生产调度方法。该方法以最长完工时间和设备总负载为目标构建多品种变批量生产调度优化模型,并基于遗传算法求解该模型。同时考虑在实际生产过程中存在的动态扰动事件,设计并实现了一种基于扰动事件驱动的重调度方法。通过对某发动机的气门传动机构进行测试,验证了文中所提方法的可行性和有效性。     

STUDY ON THE DYNAMIC SCHEDULING IN FMS REAL-TIME PRODUCTION ENVIRONMENT

0 INTRODUCTIONThe FMS scheduling task requires scheduling aset of jobs on a finite set of resources according to theproduction plans. In real manufacturing scenario, thedeterministic machine and jOb availability is neverpresent. UnfOreseen situations including machinebreakdowns, and other uncertainties inevitably resultin deviations from the generated ..h.d.l.[l]. Inresponse to changes that take place on shop floor, it isnecessary to revise the existing schedule to improvethe efficiency…     

Dynamic rescheduling in FMS that is simultaneously considering energy consumption and schedule efficiency

The dynamic rescheduling problem in flexible manufacturing systems (FMS) has historically emphasized the schedule efficiency. However, energy consumption is a basic need for different purposes in manufacturing systems around the world. This paper proposes an innovative approach to study the dynamic scheduling problem in FMS, taking the objectives of minimum or maximum energy consumption into account. A new goal programming mathematical model, which considers the energy consumption and the schedule efficiency simultaneously, is presented for solving this problem. A rescheduling method based on the genetic algorithm is introduced to address the dynamic rescheduling problem in FMS. A period policy is selected to deal with the dynamic feature of the problem. Numerical experiments have been designed to test and evaluate the performance of the proposed model. The experimental results show that the minimum energy consumption model can save the energy consumption and enhance the schedule efficiency.     

A hybrid intelligent algorithm and rescheduling technique for job shop scheduling problems with disruptions

In most real manufacturing environment, schedules are usually inevitable with the presence of various unexpected disruptions. In this study, a new rescheduling technique based on a hybrid intelligent algorithm is developed for solving job shop scheduling problems with random job arrivals and machine breakdowns. According to the dynamic feature of this problem, a new initialization method is proposed to improve the performance of the hybrid intelligent algorithm, which combines the advantage of genetic algorithm and tabu search. In order to solve the difficulty of using the mathematical model to express the unexpected disruptions, a simulator is designed to generate the disruptions. The performance measures investigated respectively are: mean flow time, maximum flow time, mean tardiness, maximum tardiness, and the number of tardy jobs. Moreover, many experiments have been designed to test and evaluate the effect of different initializations in several disruption scenarios. Finally, the performance of the new rescheduling technique is compared with other rescheduling technologies in various shop floor conditions. The experimental results show that the proposed rescheduling technique is superior to other rescheduling techniques with respect to five objectives, different shop load level, and different due date tightness. The results also illustrate that the proposed rescheduling technique has a good robustness in the dynamic manufacturing environment.     

基于强化学习的分布式光伏运维资源动态调度

针对分布式光伏运维资源调度过程中因动态因素影响导致调度计划难以实施的问题,提出基于强化学习的分布式光伏运维资源动态调度方法.该方法通过构建动态调度规则同步调整运维任务的优先级,并以新计划完成成本最低和完成时间最短为优化目标构建动态调度模型.采用Q-Learning求解模型,通过实验对比,Q-Learning算法的求解速...     

基于Agent的生产调度混合协商策略研究

当前大多协商策略无法兼顾规划和反应能力,为此,本文提出一种短期规划与动态响应能力相结合的混合协商策略。该策略针对柔性车间生产调度问题和面对扰动的再调度问题,将组合拍卖与改进合同网相结合,通过规定相关智能体的动作和交互顺序,实现系统在平稳或扰动状态下的生产调度。基于上述协商策略,开发了一个基于智能体的生产调度原型系统,并通过仿真实验验证协商策略的可行性和有效性。