A公司仓储中心出库作业优化研究

发布时间：2018-02-12 06:40

本文关键词： 仓储中心货位优化拣选路径优化遗传算法 MATLAB仿真　出处：《吉林大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着计算机信息化和机械化技术的飞速发展，仓库管理作业方式也从手工作业的传统方式向机械化作业方式转变。立体仓库是集现代物流技术和仓储技术为一体的产物。它具有占地面积小、管理成本低、存储空间大、作业响应速度快等优点，已成为现代企业物流管理系统的重要组成部分。货位优化和拣选路径优化就是以提高仓储作业效率和节约仓储成本为目标，，考虑仓储设备、货物、客户需求等各方面的问题和因素，规划货物的出入库路径和拣选作业，以提高空间利用率和货物出入库作业效率为目的，降低货物在搬运过程中不必要的损耗，降低库存成本，实现缩短货物出入库作业搬运距离和作业时间的目的，并提高仓储空间利用率。构建货位优化系统不仅可以为企业提供生产和运输准备，更能提高物流中心仓库作业效率，更好的实现企业对物流成本控制。随着主机厂的生产规模不断扩大，A公司仓储中心需要适时调整仓库管理模式来适应此变化，目前A公司仓储中心面临的主要问题为库存利用低、作业效率低，以及库存布局存在问题等。仓储中心现在急需要一种货位管理策略来解决目前遇到的问题。本文以A公司仓储中心新建立体仓库库区为研究对象，探讨货位优化在仓储中心的可行性。首先简要描述货位优化的相关理论；然后，通过对仓储中心货位管理现状的描述与分析以及对公司仓储中心的仓储管理现状以及零部件特点的分析，并根据仓储中心货位管理目标，确定以提高仓储管理效率为目标的货位优化模型，通过建模的方法将优化问题转化为可量化的数学模型，采用MATLAB软件设计算法求解最优解，并对优化前后零部件出入库作业时间进行对比分析，验证本文货位优化模型的有效性。本文通过对仓储中心拣货作业现状的分析，并根据仓储中心拣选作业的目标，确定和以拣货作业路程最短为目标的拣选路径优化模型，并利用遗传算法对优化问题进行求解；最后，选用MATLAB软件设计算法求解最优解，并对优化后结果进行分析，验证拣货路径优化模型的有效性。
[Abstract]:With the rapid development of computer information and mechanization technology, Warehouse management is also changing from traditional manual operation to mechanized work.Stereoscopic warehouse is a product of modern logistics technology and warehousing technology. It has small area, low management cost and large storage space. The quick response speed of operation has become an important part of modern enterprise logistics management system. Location optimization and routing optimization is to improve the efficiency of storage operations and save storage costs, considering storage equipment, goods, customer demand and other aspects of the problems and factors, the planning of goods access and picking operations, In order to improve the utilization ratio of space and the efficiency of loading and unloading of goods, it can reduce the unnecessary loss of goods in the course of handling, reduce the cost of inventory, and realize the purpose of shortening the distance and working time of goods in and out of storage. It can not only provide production and transportation preparation for enterprises, but also improve the efficiency of warehouse operation in logistics center, and achieve better logistics cost control. With the continuous expansion of the production scale of the mainframe factory, the warehouse center of company A needs to adjust the warehouse management mode to adapt to this change. At present, the main problems faced by the warehouse center of company A are low inventory utilization and low operation efficiency. Storage center urgently needs a kind of position management strategy to solve the current problems. In this paper, the feasibility of cargo location optimization in warehouse center is discussed by taking the newly built warehouse reservoir area of company A warehouse center as the research object. Firstly, the related theory of cargo location optimization is briefly described; then, Based on the description and analysis of the current situation of warehouse management, the present situation of warehouse management and the characteristics of parts and components, and according to the management objectives of warehouse center, The optimization model of cargo location with the aim of improving the efficiency of warehouse management is determined. The optimization problem is transformed into a quantifiable mathematical model by modeling method, and the optimal solution is solved by using MATLAB software design algorithm. The comparison and analysis of the operating time before and after the optimization verify the validity of the model. Based on the analysis of the present situation of the picking operation in the warehouse center and according to the target of the picking operation in the storage center, this paper determines and optimizes the picking path model with the shortest distance of the picking operation, and uses genetic algorithm to solve the optimization problem. Finally, the MATLAB software design algorithm is used to solve the optimal solution, and the optimized results are analyzed to verify the effectiveness of the picking path optimization model.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F252;TP18

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