U形多道式立体仓库的货位优化研究

发布时间：2018-05-12 09:18

本文选题：U形多道式 + 货位优化　；参考：《昆明理工大学》2017年硕士论文

【摘要】：当今的社会是一个多元化且快速发展的社会,现代化工业技术应运而生。传统意义上的仓储方式已经不能完全满足生产和物资流通的需要,这集中体现在货物的存储空间和摆放不够合理,存在浪费和耗时的情况,且在使用货架的过程中没有考虑对其的保护措施,加速了固定资产的损耗,使得整个的仓库工作效率偏低。在竞争激烈的现代环境下,人们的各类需求也随之增加,伴随而至的则是货物的出入库频率发生变化,所以货位的分配情况也会跟着发生变化。所以说,货位优化已然成为提升出入库效率,减少仓储投资的决定性因素。现如今单堆垛机管理单巷道的货位优化研究已经很多,优化效果显著。但对于出入库作业频率不高的部分企业来说巷道堆垛机闲置的情况尤为严重,且一台巷道堆垛机造价昂贵,造成一定的资源浪费,况且部分企业在U形模式下的货物存储效率低下,没能很好地利用其高效性。本文针对此现状对U形多道式立体仓库的模式下进行优化,即一台巷道堆垛机通过U形多道可跨越两条巷道同时管理四排货架货物的出入库作业,在提升其利用率的同时减少数量,实现保障作业要求的同时节约成本的目的。本文以全球关于货位优化的研究为理论依据,针对应该具体优化的目标建立数学模型,再通过遗传算法和粒子群算法的思想分别进行Matlab软件的编程和实现以及数据仿真优化实验后前后的对比。经过多次对所建模型的仿真后验证其理论可行,得出遗传算法在求解此类问题的效果优于粒子群算法的结论。再将遗传算法运用到实例当中,通过验证分析后达到显著的优化效果。本文旨在为企业提供一种解决实际问题的新思路,提出一种便捷且适应性强的求解货位优化的方法,帮其合理降低成本,实现利益最大化。
[Abstract]:Today's society is a diversified and rapid development society, modern industrial technology came into being. The traditional storage methods can no longer fully meet the needs of production and material circulation, which is reflected in the unreasonable storage space and placement of goods, waste and time consuming. In the process of using the shelf, the protective measures are not considered, which accelerates the loss of fixed assets and makes the working efficiency of the whole warehouse on the low side. In the competitive modern environment, people's demand also increases, and the frequency of goods entering and storing changes, so the distribution of goods will change with it. Therefore, the optimization of cargo space has become the decisive factor to improve the efficiency and reduce the storage investment. Nowadays, there are a lot of research on the cargo location optimization of single stacker crane, and the effect of optimization is remarkable. However, for some enterprises whose operation frequency is not high, the idle situation of laneway stacker is especially serious, and the cost of a laneway stacker is expensive, which results in a certain waste of resources. Moreover, some enterprises in U-mode goods storage efficiency is low, can not make good use of its high-efficiency. In view of this situation, this paper optimizes the mode of U-shaped multi-channel warehouse, that is, a tunnel stacker can cross two roadways and manage four rows of goods from and out of storage at the same time. At the same time to improve the utilization rate and reduce the number, and achieve the purpose of ensuring the operation requirements while saving costs. On the basis of the global research on cargo location optimization, this paper establishes a mathematical model for the target that should be optimized. Then the Matlab software is programmed and implemented by the idea of genetic algorithm and particle swarm optimization algorithm, and the comparison between before and after the data simulation optimization experiment is carried out. The simulation results show that the genetic algorithm is more effective than PSO in solving this kind of problem. Then the genetic algorithm is applied to an example to achieve a significant optimization effect. The purpose of this paper is to provide a new way for enterprises to solve practical problems, and to put forward a convenient and adaptable method to solve the optimization of cargo location, which can help them to reduce the cost reasonably and realize the maximum benefit.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP18;F252

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