不确定环境下Job Shop制造车间重调度驱动机制研究

发布时间：2018-05-29 20:08

本文选题：不确定环境 + 重调度执行成本　；参考：《合肥工业大学》2012年硕士论文

【摘要】：现有关于重调度驱动机制的研究中，周期性重调度、事件驱动重调度以及两者相混合的重调度虽已得到广泛的应用，但周期性重调度缺乏对突发事件的应变能力，与实时工况的耦合性不强，事件驱动的重调度易导致系统计算量过大、增大重调度频率、引起系统震荡，，而混合驱动重调度则很难协调事件驱动与周期驱动之间的关系。因此本课题以加强实时工况与调度系统的耦合性、增强系统稳定性以及最大化企业效益为目标，研究不确定环境下Job Shop制造车间的重调度驱动机制。首先分析归类Job Shop制造车间生产过程中面临的不确定因素，并通过模糊数学与径向基神经网络相结合的方法，量化其对调度系统的扰动程度；然后通过综合加权相同工序的时间偏差成本、相同工件的相邻工序的时间偏差成本、设备的工作时间偏差成本以及等待时间偏差成本，实现对重调度执行成本的衡量，并以此为基础建立预调度损失函数，同时根据重调度的优化目标建立预调度获益函数，构建损益模型；最后通过对损益模型的定量分析研究，建立基于模糊逻辑的重调度驱动机制，判断重调度的最佳决策点，以此过滤不必要的重调度，解决因频繁重调度而引起的生产系统震荡问题，降低各种不确定性问题给生产系统带来的损失，保证调度系统的有效性与稳定性。
[Abstract]:Although periodic rescheduling, event-driven rescheduling and mixed rescheduling have been widely used in the research of rescheduling drive mechanism, periodic rescheduling lacks the ability to respond to emergencies. The coupling with real-time conditions is not strong, and event-driven rescheduling can easily lead to excessive calculation, increase the frequency of rescheduling and cause system oscillation, while hybrid driven rescheduling is very difficult to coordinate the relationship between event-driven and periodic drive. Therefore, in order to enhance the coupling between real-time operation and scheduling system, enhance the stability of the system and maximize the efficiency of the enterprise, this paper studies the rescheduling driving mechanism of Job Shop manufacturing shop in uncertain environment. Firstly, the uncertain factors in the production process of Job Shop manufacturing workshop are analyzed and classified, and the disturbance degree of the scheduling system is quantified by combining fuzzy mathematics with radial basis function neural network. Then, by synthetically weighting the cost of time deviation of the same working procedure, the cost of time deviation of adjacent processes of the same workpiece, the cost of working time deviation of equipment and the cost of waiting time deviation, the cost of rescheduling execution is measured. On this basis, the loss function of pre-scheduling is established, and the profit function of pre-scheduling is established according to the optimization goal of rescheduling, and the profit and loss model is constructed. Finally, the quantitative analysis of profit and loss model is carried out. The rescheduling driving mechanism based on fuzzy logic is established to judge the optimal decision point of rescheduling so as to filter unnecessary rescheduling and solve the problem of production system shock caused by frequent rescheduling. Reduce the loss of production system caused by various uncertainty problems, and ensure the efficiency and stability of scheduling system.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH186

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