配送中心拣选作业优化研究

发布时间：2019-07-05 14:28

【摘要】：配送中心是由多个作业流程共同组成的复杂系统,其中拣选作业劳动量占配送中心总劳动量的60%左右,是配送中心主要的作业流程之一,因此拣选作业的设计与优化对配送中心的运作效率有着非常重要的影响。本文以配送中心的拣选作业为研究对象,对订单分批与拣选路径问题进行重点优化,在多台拣选设备与多个仓库储存区域并存的条件下,以订单拣选时间以及订单延迟时间加权时间最小为目标建立订单分批数学优化模型。在确定分批的基础上,以批次内订单拣选时间与订单延迟时间加权时间最小为目标,建立拣选路径优化数学模型。并将两种优化方法应用到一个算例中,期以最大限度的缩短订单拣选时间及延迟时间。对于订单分批问题,本文以拣选设备的质量与容量能力为约束,建立了以拣选时间与订单延迟时间加权时间最小为目标的数学模型。同时在包络算法分批的基础上,借鉴种子算法与节约算法分批的思想,设计了改进包络算法的订单分批启发式算法。对于拣选路径优化问题,在订单分批策略的基础上,以每一批次内订单的拣选时间与延迟时间加权时间最小为目标,建立数学优化模型,并设计了该问题的遗传算法进行求解。为了验证本文所建立的数学优化模型与所设计的相应求解算法的有效性,选取了某汽车制造企业的配送中心一段时间内的订单数据,对所建立的数学模型及算法进行验证。利用本文所设计的改进包络分批算法对订单进行分批,在分批的基础上,利用DEV C++编程求解,实现拣选路径优化问题的遗传算法。算例证明了通过先改进包络分批,后进行拣选路径优化可以最大限度的减少订单拣选时间以及订单延迟时间。
[Abstract]:Distribution center is a complex system composed of many operation processes, in which the amount of picking work accounts for about 60% of the total labor volume of distribution center, and it is one of the main operation processes of distribution center. Therefore, the design and optimization of selection operation has a very important impact on the operation efficiency of distribution center. In this paper, the picking operation of distribution center is taken as the research object, and the order batch and picking path problem is optimized. under the condition that multiple picking equipment and multiple warehouse storage areas coexist, the mathematical optimization model of order batch is established with the goal of order picking time and order delay time weighted minimum. On the basis of determining the batch, the mathematical model of picking path optimization is established with the goal of minimizing the weighted time of order picking time and order delay time in batches. The two optimization methods are applied to an example in order to shorten the order selection time and delay time to the greatest extent. For the order batching problem, this paper takes the quality and capacity of the picking equipment as the constraint, and establishes a mathematical model aimed at the minimum weighted time of the picking time and the order delay time. At the same time, based on the batch of envelope algorithm and the idea of seed algorithm and saving algorithm, an order batch heuristic algorithm is designed to improve the envelope algorithm. For the picking path optimization problem, based on the order batch strategy, the mathematical optimization model is established with the goal of minimizing the picking time and delay time weighted time of each batch of orders, and the genetic algorithm is designed to solve the problem. In order to verify the effectiveness of the mathematical optimization model and the corresponding algorithm designed in this paper, the order data of the distribution center of an automobile manufacturing enterprise for a period of time are selected, and the established mathematical model and algorithm are verified. The improved envelope batch algorithm designed in this paper is used to batch the order. On the basis of batch, DEV C programming is used to solve the problem, and the genetic algorithm for picking path optimization problem is realized. The example shows that the order selection time and order delay time can be minimized by improving the envelope batch first and then optimizing the picking path.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F252.1

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