柔性作业车间的多目标动态稳健调度研究

发布时间：2019-05-17 19:59

【摘要】：车间调度方法与优化技术的研究已经成为先进制造技术的基础和关键。在制造业车间,调度问题的规模巨大,所涉及的对象复杂。调度优化问题通常是多目标的,而且各目标之间往往存在冲突。此外,实际生产过程中还存在着不确定的扰动因素,比如：机器故障、加工时间改变,紧急插单等。因此,对车间调度问题进行深入的研究,能够更好的指导生产。论文正是在这样的背景下,结合实际生产调度问题所面临的多目标和动态性等问题,对柔性作业车间的多目标调度问题进行了研究,并取得了一些有意义的研究成果。论文的主要工作为： (1)对车间调度问题的研究背景,研究现状以及研究趋势进行总结；对现有的车间调度算法进行对比分析；阐述了本课题的研究意义和研究目的。 (2)对多目标优化算法进行分析,强调进化算法相对于传统多目标算法的优势。并基于工件目标的不同,提出了柔性作业车间的多目标调度问题的评价指标体系。该体系包含时间、机器负荷、成本、交货期在内的柔性作业车间的调度目标,并讨论了各目标的计算方法。 (3)根据实际制造系统中关注最多的最大完成时间最小和提前／拖期惩罚最小为目标,建立了柔性作业车间的多目标的调度模型。另外,论文提出一种包含扰动事件评估、缓冲整合、局部更新、完全重调度的多级动态稳健调度策略,弥补了当前对如何减少完全重调度的次数,保证调度方案的连续性和稳健性方面存在的缺陷。 (4)对求解柔性作业车间的多目标调度问题的遗传算法进行改进,将免疫算法引入遗传算法中,利用免疫和熵原理维持种群的多样性；另外,针对多目标遗传算法在精英选择策略方面的不足,引入了分布函数,最后通过实例验证了算法的可行性。 (5)针对实际制造车间动态性的特点,提出了一种基于滚动窗口的多目标免疫遗传算法策略。该策略基于周期和事件驱动的再调度机制将调度过程分成一系列连续的静态调度区间,在每个区间内用基于Pareto概念的多目标免疫遗传算法进行优化调度。并根据调度模型目标的设置,提出了相对应的窗口工件选取原则。 (6)对完全重调度的稳健性进行分析、设计。根据柔性作业车间的特点,设计了扩展的偏离度指标,该指标充分考虑了工件和机器在保持调度稳健性方面的作用。与多级动态稳健调度共同保证了调度方案的连续性和稳健性。
[Abstract]:The research of job shop scheduling method and optimization technology has become the basis and key of advanced manufacturing technology. In manufacturing workshop, the scale of scheduling problem is huge and the object involved is complex. Scheduling optimization problems are usually multi-objective, and there are often conflicts between the objectives. In addition, there are uncertain disturbance factors in the actual production process, such as machine failure, processing time change, emergency list insertion and so on. Therefore, the in-depth study of job shop scheduling problem can better guide production. Under this background, combined with the multi-objective and dynamic problems faced by the actual production scheduling problem, the multi-objective scheduling problem of flexible job shop is studied, and some meaningful research results are obtained. The main work of this paper is as follows: (1) the research background, research status and research trend of job shop scheduling problem are summarized; the existing job shop scheduling algorithms are compared and analyzed; and the research significance and purpose of this topic are expounded. (2) the multi-objective optimization algorithm is analyzed, and the advantages of evolutionary algorithm over the traditional multi-objective algorithm are emphasized. Based on the difference of workpiece objectives, the evaluation index system of multi-objective scheduling problem for flexible job shop is proposed. The system includes the scheduling objectives of flexible job shop, such as time, machine load, cost and delivery time, and discusses the calculation method of each objective. (3) according to the goal of minimum maximum completion time and minimum penalty of advance / delay in the actual manufacturing system, a multi-objective scheduling model of flexible job shop is established. In addition, this paper proposes a multi-level dynamic robust scheduling strategy, which includes disturbance event evaluation, buffer integration, local update and complete rescheduling, which makes up for the current number of times of complete rescheduling. The defects in ensuring the continuity and robustness of the scheduling scheme. (4) the genetic algorithm for solving the multi-objective scheduling problem in flexible job shop is improved. The immune algorithm is introduced into the genetic algorithm, and the immune and entropy principles are used to maintain the diversity of the population. In addition, aiming at the shortcomings of multi-objective genetic algorithm in elite selection strategy, the distribution function is introduced, and an example is given to verify the feasibility of the algorithm. (5) according to the dynamic characteristics of the actual manufacturing workshop, a multi-objective immune genetic algorithm (IGA) strategy based on rolling window is proposed. Based on the periodic and event-driven rescheduling mechanism, the scheduling process is divided into a series of continuous static scheduling intervals, and the multi-objective immune genetic algorithm based on Pareto concept is used to optimize the scheduling in each interval. According to the setting of the goal of the scheduling model, the corresponding principle of window workpiece selection is put forward. (6) the robustness of complete rescheduling is analyzed and designed. According to the characteristics of flexible job shop, an extended deviation index is designed, which fully takes into account the role of workpiece and machine in maintaining scheduling robustness. Together with multi-level dynamic robust scheduling, the continuity and robustness of the scheduling scheme are guaranteed.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TB497

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