基于混合遗传禁忌搜索算法的多目标柔性作业车间调度问题研究

发布时间：2018-01-06 22:06

  本文关键词：基于混合遗传禁忌搜索算法的多目标柔性作业车间调度问题研究　出处：《重庆大学》2012年硕士论文　论文类型：学位论文

  更多相关文章： 工件目标差异 多目标柔性作业车间调度 混合遗传禁忌搜索算法 多目标计算方法 双资源约束

【摘要】：车间调度是制造型企业生产管理的核心部分，对企业的盈利能力有着举足轻重的作用。历经半个多世纪，针对经典作业车间调度问题的研究已经取得了丰富的理论成果，但是所建立的模型还不能很好的反映实际生产，不能很好的指导生产。而在经典作业车间调度问题基础上发展来的多目标柔性作业车间调度问题，能够综合考虑企业内部各部门的决策期望，更好的适应现代生产模式的需求，对其研究有着重要的理论意义和实践意义。 本文在经典作业车间调度的基础上，描述了柔性作业车间调度问题，并对多目标柔性作业车间调度问题进行了建模，，设计了求解算法，主要内容如下： ①提出了包括最大完工时间、平均流经时间、瓶颈机器总负荷、机器总负荷、工件交货期、工件加工成本、产品质量的多个目标，并引入了基于工件目标不同的多目标优化概念，并给出了各目标的计算方法。 ②针对工件目标不同的多目标调度问题提出了一种混合遗传禁忌搜索算法，并采用了一种基于工序和机器的编码方式，以及新型的基于工序和机器的交叉方式，建立了调度算法。 ③分析了目前常用的多目标优化算法，并选定了一种改进的NSGA-ⅡPareto排序方法。 ④建立了更贴近实际生产的基于工件加工目标不同的多目标柔性作业车间调度问题模型，并提出了以机床和工人为双约束，工件交货期为主要目标，总加工成本、瓶颈机器总负荷、总完工时间、单件工件加工成本、单件工件加工质量、单件工件完工时间为次优化目标的调度模型。 ⑤以实际项目为基础，对上述模型进行了仿真，验证了模型和算法的有效性。
[Abstract]:Job shop scheduling is the core part of production management in manufacturing enterprises, which plays an important role in the profitability of enterprises and has lasted for more than half a century. The research on the classical job shop scheduling problem has made a lot of theoretical achievements, but the established model can not well reflect the actual production. The multi-objective flexible job shop scheduling problem developed on the basis of the classical job shop scheduling problem can comprehensively consider the decision-making expectations of various departments within the enterprise. It is of great theoretical and practical significance to better adapt to the demand of modern production mode. Based on the classical job shop scheduling, the flexible job shop scheduling problem is described in this paper, and the multi-objective flexible job shop scheduling problem is modeled, and a solution algorithm is designed. The main contents are as follows: The main contents are as follows: (1) multiple objectives including the maximum completion time, the average flow time, the total load of the bottleneck machine, the total load of the machine, the delivery time of the workpiece, the processing cost of the workpiece, and the quality of the product are proposed. The concept of multi-objective optimization based on different object of workpiece is introduced, and the calculation method of each target is given. 2. A hybrid genetic Tabu search algorithm is proposed for multi-objective scheduling problem with different job targets, and a coding method based on process and machine is adopted. And a new scheduling algorithm based on process and machine intersection is established. 3. The commonly used multi-objective optimization algorithm is analyzed, and an improved NSGA- 鈪

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