摘要
随着农产品供应链智能化转型的深入推进,配送中心作为连接产地与消费者的关键枢纽,其运行效率直接影响食品损耗率与物流成本。本文针对农产品易腐性、时效性与季节性波动带来的运营挑战,基于多方法仿真平台Anylogic,构建了一个面向农产品配送中心的动态仿真模型。模型融合离散事件仿真、系统动力学与基于主体的建模方法,对货物入库、分拣、加工、存储及出库全流程进行数字化映射。通过案例数据驱动仿真实验,重点优化流通加工区作业流程与资源调度策略。结果表明,通过分区作业与流程重构,加工区拥堵率降低约40%,整体作业效率提升25%,同时可降低生鲜损耗约15%。本研究为农产品配送中心的流程优化与系统韧性提升提供了可操作的仿真支持,对推动农产品物流绿色化、智能化发展具有理论与实践意义。
With the deepening intelligent transformation of the agricultural product supply chain,the distribution center,as a critical hub connecting production areas with consumers,has its operational efficiency directly impacting food loss rates and logistics costs.Addressing the operational challenges posed by the perishability,timeliness,and seasonal fluctuations of agricultural products,this paper constructs a dynamic simulation model for an agricultural product distribution center based on the multi-method simulation platform AnyLogic.The model integrates Discrete Event Simulation,System Dynamics,and Agent-Based Modeling methods to digitally map the entire process including goods receiving,sorting,processing,storage,and shipping.Driven by case data,simulation experiments were conducted,focusing on optimizing the workflow and resource scheduling strategies in the valueadded processing area.The results indicate that through zoned operations and process reengineering,congestion in the processing area was reduced by approximately 40%,overall operational efficiency improved by about 25%,and fresh product loss could be reduced by around 15%.This research provides actionable simulation support for process optimization and system resilience enhancement in agricultural product distribution centers,holding theoretical and practical significance for promoting the greening and intelligent development of agricultural product logistics.
作者
王雨晴
王筱
胡建武
WANG Yuqing;WANG Xiao;HU Jianwu(Qingdao City University,Qingdao 266109,China;Shandong Cultural Industry Vocational College,Qingdao 266600,China)
关键词
农产品配送中心
Anylogic仿真
易腐品物流
流程优化
系统韧性
agricultural product distribution center
Anylogic simulation
perishable product logistics
process optimization
system resilience
