基于模糊时间窗的智慧物流越库调度仿真研究  

Smart Logistics Vietnamese Database Simulation Simulation Study Based on the Vagogy Time Window

作　　者：李平 牛进[1] LI Ping;Niu Jin(Zhengzhou University of Industrial Technology,Zhengzhou Henan 451100,China;Shandong University of Science and Technology,Qingdao Shandong 266590,China)

机构地区：[1]郑州工业应用技术学院,河南郑州451100 [2]山东科技大学,山东青岛266590

出　　处：《计算机仿真》2024年第3期110-113,523,共5页Computer Simulation

基　　金：河南省哲学社会科学规划项目(2017CJJ099);河南省科技厅软科学项目(192400410295)。

摘　　要：在越库配送中商品和货物到了配送中心后直接可在站台上向客户配送,能够有效降低库存和运输成本,但是对车辆调度效率要求较高。若进出站台的车辆得不到精准排序,会直接影响货物出站时间。为进一步提升越库调度效果,提出基于模糊时间窗的智慧物流越库调度方法。基于物流越库类型的分析结果,结合模糊时间窗制定调度目标函数以及约束条件,构建物流越库调度模型。引入萤火虫算法对调度模型求解,获取模型最佳目标函数值,输出模型调度结果,实现智慧物流的越库调度。实验结果表明,上述方法对物流越库调度模型的求解与最优解的差距最小,且物流调度范围对其影响不大,可在10s之内完成智慧物流的越库调度,应用效率较高。At present,goods can be directly distributed to customers on the platform after arriving at the distribution center,which effectively reduces the costs,but requires higher efficiency of vehicle scheduling.If the vehicles entering and leaving the station can't be sorted accurately,it will directly affect the time of goods leaving the station.In order to further improve the cross-docking scheduling effect,this paper puts forward an intelligent cross-docking scheduling method based on fuzzy time window.Based on the analysis of cross-docking type and fuzzy time window,the objective function and constraint conditions of cross-docking scheduling were formulated,and then a crossdocking model was constructed.Moreover,the firefly algorithm was introduced to solve the model,thus obtaining the optimal objective function value of the model.Finally,the scheduling result was output,thus achieving the cross-docking scheduling of intelligent logistics.Experimental results prove that the proposed method has minimal gap between the actual solution and the optimal solution,as well as low logistics scheduling influence.The cross-docking scheduling of intelligent logistics can be completed within 10s,and the application efficiency is higher.

关 键 词：模糊时间窗 智慧物流 越库调度方法 调度模型 萤火虫算法 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]