自动化立体仓库存取作业调度两阶段优化研究

发布时间：2018-06-21 07:13

本文选题：自动化立体仓库 + 货位分配　；参考：《重庆工商大学》2015年硕士论文

【摘要】：在现代物流系统中,自动化立体仓库作为其中的重要组成部分,集存储、搬运和配送于一体,在现代化企业中发挥了重大的作用。自动化立体库是一个综合复杂的自动化系统,它的存取作业调度问题直接影响着整体系统的工作效率。为了有效地管理和提高系统整体的作业效率,必须对其存取作业调度进行优化,从而减少货物的移动距离和存取时间,以此最终提高企业经济效益。因此,本文对自动化立体仓库存取作业调度两阶段优化的研究有着重要的理论意义和实际应用价值。本文的研究就以下几方面开展:阐述了选题的背景、相关文献综述和主要内容,即研究的主要问题和工作。并详细地介绍了相关理论,主要包括自动化立体仓库方面的理论和求解算法等。这些理论研究都为之后开展研究工作建立良好基础。重点研究自动化立体仓库存取作业调度两阶段的优化。存取作业调度包括两个过程,第一个过程是货位分配,第二个过程是存取作业路径。所以两阶段优化的过程为,第一阶段对货位分配的优化研究,第二阶段在货位分配的基础上进行存取作业路径优化研究。首先分别描述了货位分配和存取作业路径问题,然后第一阶段提出了货位分配的数学模型,针对该模型给出了求解的算法。第二阶段是在货位分配的基础上以最小化堆垛机对周期内全部物料完成存取作业的总时间作为优化目标,以分类存储的堆垛机复合和单一作业共同执行的方式为研究对象,提出了存取作业路径优化的模型。针对该模型,提出了两种算法,一种是基于寻找离原点(出入库台)最近且时间最短货位策略的遗传算法,另一种是基于寻找离原点(出入库台)最近且时间最短货位策略的遗传退火算法,分别给出两种算法的实现步骤,为解决实际问题提供了理论方法。最后通过MATLAB对算法运行求解,FLEXSIM仿真软件对优化模型进行可视化仿真研究。针对某个仿真算例,按照两阶段优化的思路,先进行货位分配优化,根据确定的货位,进行第二阶段的存取作业调度研究,基于已提出的模型和算法,给出了六种仿真方案。经过仿真结果分析可知,两阶段优化模型是有效的,并通过多次运行模型验证表明所提的方法是有效的。
[Abstract]:As an important part of modern logistics system, automated warehouse plays an important role in modern enterprises by integrating storage, transportation and distribution. Automated stereo library is a complex automation system, its access job scheduling problem directly affects the working efficiency of the whole system. In order to effectively manage and improve the operation efficiency of the whole system, it is necessary to optimize the scheduling of the access jobs so as to reduce the moving distance and access time of the goods, and finally improve the economic benefits of the enterprises. Therefore, this paper has important theoretical significance and practical application value to the research of two-stage optimization of access job scheduling in automated warehouse. The research in this paper is carried out in the following aspects: the background of the topic, the relevant literature review and main contents, namely the main problems and work of the research. The related theories are introduced in detail, including the theory and algorithm of automated warehouse. These theoretical studies have established a good foundation for the later research work. This paper focuses on the optimization of two stages of access job scheduling in automated warehouse. Access job scheduling consists of two processes: the first is the allocation of cargo spaces and the second is the access job path. So the process of two-stage optimization is as follows: the first stage is the optimization of the allocation of cargo space, the second stage is on the basis of the allocation of the cargo location, and the second stage is based on the optimization of the access operation path. Firstly, the location assignment and access operation path problems are described respectively. Then, in the first stage, the mathematical model of cargo location assignment is proposed, and the algorithm for solving this model is given. The second stage is to minimize the total time for the stacker to complete the access operation of all the materials in the cycle on the basis of the distribution of the cargo position. The research object is the combination of the classified storage stacker and the single job as the research object. A model of access job path optimization is proposed. For this model, two algorithms are proposed, one is genetic algorithm based on finding the nearest and shortest time position strategy to the origin. The other is based on the genetic annealing algorithm, which is based on finding the nearest and shortest time position strategy from the origin. The implementation steps of the two algorithms are given respectively, which provide a theoretical method for solving the practical problems. Finally, the optimization model is visualized and simulated by MATLAB with FLEXSIM simulation software. Aiming at a certain simulation example, according to the idea of two-stage optimization, this paper first optimizes the allocation of cargo space, and according to the determined location, carries out the second stage access job scheduling research. Based on the proposed model and algorithm, six simulation schemes are presented. The simulation results show that the two-stage optimization model is effective and the proposed method is proved to be effective by several running models.
【学位授予单位】：重庆工商大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F252.1

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