电子商务环境下在线订单拣选策略设计研究

In recent years, with the development of e-commerce, in order to enhance the service level, online retailers and distribution centers should provide accurate and timely logistics services to match the explosive growth of online orders. As one of the most important operation activities in warehouse management, order picking should be improved and adapted for online order services. However, due to the characteristics of online orders, namely, demand fluctuations, time-varying arrival rate of order, and the variations in order size, most traditional picking strategies for offline order are no longer suitable for online environment. Based on the quantitative analysis of the characteristics of online orders, this project will firstly design new order picking strategies via deep learning, heuristic rules and meta-heuristics for online order picking activities, including storage assignment, zoning, batching and routing. Secondly, based on newly developed multi-agent simulation platforms for online order picking, the efficiency of new strategies and the impact of the online orders on the picking throughput will be investigated. This project will finally bring original research achievements on the design, optimization, simulation and analyzing for the order picking strategies, which will certainly contribute to the fields of order picking and supply chain management.

近年来，随着电子商务的发展，为了提高竞争力，电商企业与配送中心需要为数量呈爆炸式增长的在线订单提供准确及时的物流服务。作为仓储系统运营中的关键环节，订单拣选作业也必须针对在线订单做出相应的优化。然而，在线订单所反映出的产品需求波动性、到达速率时变性、订单尺寸易变性等特性，使得大多数基于传统离线环境假设的拣选策略变得不再适用。本课题以电子商务企业的订单拣选问题为研究背景，从定量分析在线订单的特性出发，针对货位分配、作业分区、订单分批、拣选路线规划等不同环节，利用深度学习、启发式规则、智能优化算法以及多主体仿真实验等研究方法，为这些环节设计出适应电商环境的作业策略。随后，在建立在线订单拣选策略设计综合实验平台的基础上，验证作业策略的有效性，研究在线订单特性对拣选效率的影响。本课题力图在针对电子商务环境的订单拣选策略设计、优化、仿真与分析等方面取得原创性成果，促进仓库运作和供应链管理的研究。

电商环境对传统仓库作业中的订单拣选作业环节带来了挑战。本项目以电商环境为背景，围绕订单拣选作业，分别研究了在线订单的产品需求波动性、到达速率时变性、订单尺寸易变性以及现实仓库布局复杂性共同作用下的布局设计、货位分配、作业分区、订单分批、拣选路线规划、打包等环节的策略设计问题。通过综合运用启发式算法、智能优化算法、多主体仿真等手段，我们提出了考虑订单尺寸易变性的订单组批-打包集成策略、考虑超窄通道和访问限制的拣选路线算法、建设了描述电商物流作业的多主体虚拟仿真教学实验平台。通过这些研究，我们揭示了电商环境对订单拣选作业的影响规律。本项目也拓宽了研究领域，将复杂网络理论应用到标准起草单位贡献分析、工程安全强化策略设计等问题。本项目的研究对于提高电商订单拣选效率具有重要意义。