OMO模式下社区生鲜超市拣货与多温共配在线联合调度问题研究

The Online-Merge-Offline community fresh supermarket is an innovative fresh e-commerce mode. The online orders are processed by the nearest suppermarket, by picking up and delivery. This mode can service the customer around 3 kilometers within one hour. However different food needs to be stored and delivered in different temperature zones, which increases the difficulty of order fulfillment. The orders arrive dynamically, which increases the difficulty of real-time optimization. The key problem of online order fulfullment is how to formulate an efficient picking and delivery scheduling rules to control logistics cost, ensure food freshness and delivery efficiency. This project is proposed to integrate the picking and delivery processes to improve the overall optimization space. The objective is to explore integrated online scheduling methods of order picking and delivery under community fresh supermarket. Firstly, the comprehensive assessment methods of the multiple-temperature fresh food under picking and delivery processes are studied. Secondly, the multiple-zone order batching strategies considering freshness are studied. Moreover the multiple-temperature joint delivery model under community fresh supermarket is studied. Finally, according to the close relationship between picking and delivery, the dynamic scheduling rules of picking and multiple-temperature joint delivery considering freshness are designed. The achievements are intended to enrich the order picking theory, integrated online production and delivery theory. Moreover the achievements can provide theoretical support for the rapid development of China's fresh e-commerce industry.

OMO（Online-Merge-Offline）模式下的社区生鲜超市是生鲜电商的创新运营模式，采用线上下单线下门店就近拣货并配送，实现“门店3公里范围内1小时送达”的高效服务。但不同温区产品需分区存储和配送，增加订单履行难度；订单动态达到，加大实时优化难度。如何制定高效的拣货和配送在线调度策略，控制物流成本，同时保证产品新鲜度和配送时效，是当前线上订单履行的关键难题。本项目尝试整合拣货和配送操作以提升整体优化空间，探索社区生鲜超市线上订单拣货与配送在线联合调度方法。首先研究拣货与配送环节下不同温区产品的新鲜度综合评估方法；其次研究考虑新鲜度的多分区货架订单分批拣货策略，及适用社区生鲜超市的储冷式多温共配策略。最后依据拣货与配送的紧密关联性，设计考虑新鲜度的拣货与多温共配问题动态调度规则。研究成果旨在丰富订单拣货优化理论和生产与配送在线调度理论，并为我国生鲜电商行业快速发展提供理论支撑。

O2O模式下的社区生鲜超市采用线上下单线下门店就近拣货并配送，实现“门店3公里范围内1小时送达”的高效服务。如何制定高效的拣货和配送在线调度策略，控制物流成本，同时保证产品新鲜度和配送时效，是线上订单履行的关键问题。本项目采用订单拣选、车辆路径规划、生产与配送联合调度等理论，基于在线算法、启发式算法等求解方法，构建一套适用于O2O模式下社区生鲜超市线上订单拣货与配送在线联合调度方法。.首先，研究高效的订单拣选策略，设计考虑产品品类约束的订单分批与拣选路径优化调度算法，以及考虑产品品类约束的订单分批与装箱调度算法。然后，将社区生鲜超市中的拣选与配送联合调度问题转化为一类特殊的生产与配送联合调度问题，并设计一系列不同场景下的在线调度算法。最后，将拣选员工的行为因素引入线上订单履行问题中，对员工的学习和遗忘效应进行量化分析，并深入研究学习-遗忘效应对拣选效率的影响。.项目提出的一系列调度算法既能提高拣选与配送效率，降级订单履行成本，同时可以避免食品与非食品在拣选和配送过程中接触产生污染，保障食品安全。以员工行为因素为视角研究学习和遗忘效应的拣选效率的影响，有助于提升拣选效率的评估的可预测性和准确性，并得出提高员工工作效率的相关结论。.社区电商等新兴电子商务应用中的订单履行过程同样符合生产与配送联合调度的特征，本项目提出的一系列模型和算法可进一步应用到更广泛的电子商务订单履行场景当中，为管理人员提供一套有效的订单履行策略方案。.