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需求导向的智能快件箱格口数量优化
Optimization of Compartment Number of Intelligent Self-express Service Machine under Demand Orientation
【摘要】 为了研究智能快件箱格口数量优化配置问题,采用多目标建模方法,考虑智能快件箱的固定成本、变动成本及因格口不足或闲置造成的机会成本,建立了智能快件箱布置总成本与用户满意度的多目标格口数量优化模型。分析了智能快件箱现有格口规格种类,发现其与实际需求不完全匹配,因而提出格口规格改进策略,在原有标准组规格的基础上增设短组格口,每组又分为3种不同大小规格,共两组6种规格。在针对性设计编码的基础上采用带收敛速度控制的粒子群算法对模型进行求解,并以500次求解结果的均值作为输出来减少随机变量对结果的影响。通过引入算例对模型的有效性进行了验证,并在需求导向下对快递量、配送快递中各种规格的比例及用户取件习惯3种影响因素进行了灵敏度分析。结果表明:与经验布置方案相比总成本降低了24%,整体闲置率下降了20%;灵敏度分析结果显示快递量的增加相较于其减少会导致格口需求数量更为明显的变化,并且不同规格的格口对需求量变化的敏感程度也不相同;标准组大格口、短组大格口和小格口的需求数量对各种尺寸快递的比例值变化敏感程度不高,另外3种随着比例的变化会有明显的波动;用户延迟取件比例的增加会带来格口需求数量显著的变化。
【Abstract】 To study the optimal layout of the number of compartments in intelligent self-express service machine, by adopting the multi-objective modeling method, considering fixed cost, variable cost and opportunity cost due to insufficient or idle compartment, the multi-objective optimization model of compartment quantity with total cost and customer satisfaction of the layout is established. The specifications and types of existing compartments for intelligent self-express service machine are analyzed. It is found that they do not completely match the actual needs. Therefore, a specification improvement strategy is proposed. A short group of compartments is added on the basis of the original standard group specifications, and each group is divided into 3 specifications, a total of 2 groups and 6 specifications. On the basis of the targeted design code, the PSO with convergence speed control is used to solve the model, and the average value of 500 solving results is used as the output to reduce the influence of random variables on the result. The effectiveness of the model is verified by introducing a calculation example, and the sensitivity analysis of the 3 influencing factors(express delivery volume, proportion of various specifications in the express delivery, and user’s pick-up habit) is carried out under the demand orientation. The result shows that(1) compared with the experience layout scheme, the total cost is reduced by 24% and the overall idle rate is reduced by 20%;(2) the result of sensitivity analysis indicates that the increase in express delivery volume will lead to more obvious changes in the demand number of compartments than the decrease, and the sensitivity of different specifications to the changes in demand is also different;(3) the demand for 3 types of compartment(big in standard group, big and small in short group) are less sensitive to the change of the proportion value of various express sizes, while the demand for the other 3 types will fluctuate significantly with the change of the proportion;(4) the increase in the proportion of users’ late pick-up will bring about a significant change in the number of grid demand.
【Key words】 logistics engineering; compartment number; multi-objective model; intelligent self-express service machine; particle swarm optimization(PSO);
- 【文献出处】 公路交通科技 ,Journal of Highway and Transportation Research and Development , 编辑部邮箱 ,2021年01期
- 【分类号】TP18;F259.2
- 【下载频次】116