电商订单拣选与配送的联合调度优化——基于考虑货箱卸货顺序约束的改进模拟退火算法

Joint Scheduling Optimization for E-commerce Order Picking and Delivery--Based on an Improved Simulated Annealing Algorithm with Consideration of Cargo Box Unloading Sequence Constraints

在电商物流环境下货箱在送货车辆中的堆码方式会影响订单拣选与配送的整体服务效率,文章综合考虑了配送过程中的卸货顺序约束,分析了不同堆码方式对卸货效率、拣选顺序和分批方案的影响。以拣选时间和卸货时间最短为目标,构建了考虑货箱卸载顺序约束的订单拣选与配送联合调度模型(IOPDS-BUS),并设计了改进的模拟退火算法(ISA)以获得更高效的堆码方式、分批方案与拣选顺序。结果表明,ISA算法能够解决IOPDS-BUS问题,且优于传统算法;IOPDS-BUS可以提高物流中心的整体配送效率。同时,在物流配送实践中,很难同时优化拣选时间和卸货时间,但可以拣选时间为代价优化卸货时间,从而降低物流成本,提高整体配送效率。

In e-commerce logistics,the stacking method of cargo boxes in delivery vehicles impacts the overall efficiency of order picking and delivery.This paper considers the constraints of the unloading sequence during the delivery process and analyzes how different stacking methods affect unloading efficiency,picking order,and batching strategies.Aiming to minimize the time spent on picking and unloading,an Integrated Order Picking and Delivery Scheduling model(IOPDS-BUS)that takes into account cargo box unloading sequence constraints has been developed.Furthermore,an Improved Simulated Annealing algorithm(ISA)has been proposed to find more efficient stacking methods,batching strategies,and picking sequences.The results demonstrate that the ISA algorithm can effectively address the IOPDS-BUS problem and outperforms traditional algorithms.Moreover,the IOPDS-BUS model can enhance the overall efficiency of logistics centers.However,in practical logistics operations,optimizing picking and unloading times simultaneously is challenging,but it is feasible to improve unloading time at the expense of picking time,thus lowering logistics costs and enhancing overall delivery efficiency.