车辆货物配装过程建模与优化决策

以家电企业配送为例研究车辆和多品种货物的配装问题。以配送中心车辆运力最大化为目标,研究如何对货物进行装车调配、优化处理来提高车辆的装载效率,以降低配送运输成本。对车辆类型、体积、载重额、客户优先级以及按区域配送线路等约束条件和目标函数进行系统分析,建立车辆货物配装数学模型。运用物流仿真软件建立货物配装的动态仿真模型,用遗传算法对配装过程进行优化,得出装载货物顺序编号的决策方案。仿真统计结果分析表明该仿真模型可以使顾客需求货物满足车辆容重约束并按优先级依次装车时的价值最大,车辆的载重量和有效容积利用率达到90%以上,降低了配送成本。

Modeling and optimization of vehicle goods loading

Taking the home appliances enterprise as the example,the paper studies the loading of vehicles and multi-category goods.Taking the maximum transport capacity of vehicles at the distribution center as the objective,the paper researches how to enhance the vehicle loading efficiency by loading adjustment and optimization,to reduce the distribution and transportation costs.The paper applies system analysis to the constraints like vehicle type,volume,carrying capacity,customer priority,and regional distribution lines as well as objective function,to build the mathematical model of the vehicle goods loading.With the logistics simulation software,the paper develops the dynamic simulation model of goods loading,optimizes the loading process with genetic algorithm,thus to obtain the decision-making program of goods loading sequence.Simulation results show that the highest value of vehicle loading appears when the vehicle is loaded according to customer priority and vehicle density and the utilization of the vehicle loading mass and effective volume reaches 90%,thus reducing the distribution costs.