智能仓储 AGV 与拣货工作站动态配置模型研究

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DOI：10.19981/j.CN23-1581/G3.2026.12.008

中图分类号：TP399

文献标志码： A

文章编号：2095-2945（2026）12-0029-04

Abstract： To address the issues of mismatched configuration between AGVs and workstations in smart Warehousing， as well as the inability of static schemes to cope with demand fluctuations， an online mixed-integer linear programming （MILP） model is constructed to achieve dynamic optimization of resources under the condition of known hourly picking quantities. The model aims to minimize costs， incorporates hard constraints such as production capacity constraints and resource upper limit constraints， and realizes hourly real-time solution by handling nonlinear relationships through piecewise linearization. Verified with data from the first week of September， the model can meet 100% production capacity demand， resource consumption is highly matched with order volume， and the cost is significantly reduced compared with the fixed configuration， providing a feasible mathematical optimization solution for smart Warehousing to efficiently respond to order fluctuations. The optimized plan can provide technical support for the goal of "improving quality and efficiency of smart logistics" in the "14th Five-Year Plan" modern logistics development plan， promote the digital transformation of the warehousing link， help the logistics industry break through resource constraints， improve the resilience and response speed of the supply chain， and provide replicable solutions to deal with order fluctuations.

Keywords： smart Warehousing; dynamic resource allocation; mixed integer linear programming （MILP）; AGV scheduling; capacity constraint

智能仓储作为供应链核心枢纽，出库拣货效率直接影响企业竞争力，但“忙闲不均”“挂单风险”等问题凸显。（剩余6059字）