自动化立体仓库堆垛机调度问题研究

发布时间：2018-10-21 10:34

【摘要】：在现代物流技术领域中,新产生了一个存储模式,即为自动化立体仓库,在一定程度上影响了工业生产,并在工业生产中起着极其重要的作用。本文的主要研究内容如下:(1)现代物流系统中优化自动化立体仓库调度起着极其重大得影响;为了更好的进行后文的建模和优化调度问题,在第一章中介绍自动化立体仓库的基本概念及其结构。(2)以对自动化立体仓库的入库货位分区及货位分配问题进行了详细介绍,分别阐述了自动化立体仓库的分区和分配原则,并建立了货位优化数学模型及货位分配优化模型。(3)对堆垛机的调度和调度优化目标的进行了分析,对堆垛机五种常见停留策略进行了讨论,并分析比较五种停留策略性能优劣。(4)为了更好的优化堆垛机拣选作业和复合作业,详细分析堆垛机作业方式的特点,并针对这两种作业方式提出了优化方法。对于拣选作业,提出了含周转货箱容量限制作业调度,重新构建数学模型。对模型进行分析,发现该模型为NP完全问题,对这个模型求解的方法可采用遗传算法。对于复合作业,经过适当转换规则发展,把这类作业调度问题转变成旅行商问题,优化复合作业这种作业方式的方法可采用遗传算法。通过仿真验证以上两种作业方式的优化,和随机调度相比较,结果表明,该优化算法可大大缩短调度的运行时间。
[Abstract]:In the field of modern logistics technology, a new storage mode has emerged, that is, automatic three-dimensional warehouse, which has affected industrial production to a certain extent and played an extremely important role in industrial production. The main contents of this paper are as follows: (1) the optimization of automated warehouse scheduling in modern logistics system plays an extremely important role; In the first chapter, the basic concept and structure of automated warehouse are introduced. (2) the partition and distribution of storage space are introduced in detail, and the partition and distribution principle of automated warehouse are expounded respectively. The mathematical model of cargo location optimization and the optimization model of cargo location allocation are established. (3) the scheduling and scheduling optimization objectives of the stacker are analyzed, and five common stopover strategies of the stacker are discussed. The performance of the five stopover strategies is analyzed and compared. (4) in order to optimize the picking and composite operations of the stacker, the characteristics of the stacker operation are analyzed in detail, and the optimization methods are proposed. For the picking operation, a new mathematical model is proposed, which includes the limited capacity of the container and the scheduling of the operation. By analyzing the model, it is found that the model is a NP complete problem, and the genetic algorithm can be used to solve the model. For compound jobs, after proper transformation rules, this kind of job scheduling problem is transformed into traveling salesman problem. Genetic algorithm can be used to optimize the operation mode of compound jobs. The simulation results show that the proposed optimization algorithm can greatly shorten the scheduling time compared with the random scheduling.
【学位授予单位】：沈阳大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F252;TP18

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