高铁场景下的无人零售终端补货供应链调度优化研究

Optimization of Replenishment Supply Chain Scheduling of Smart Vending Machines under High-speed Railway Scenarios

无人零售终端作为新零售的形式之一,已经被应用于多种不同的场景,但这些场景往往是静态的。如今,高铁等动态场景对于无人零售的需求日益凸显,但流动场景中无人零售终端的补货往往会受到时间和空间的双重制约,这对实现合理补货的供应链调度优化过程提出了新的挑战。本文从高铁场景的特殊性入手,通过深入分析高铁场景的特征及其需求特点,搭建了符合高铁场景要求的补货供应链调度多维度评价体系,在此基础上构建了高铁场景下无人零售终端的补货供应链调度优化数学模型,并探讨了求解算法。最后,通过算例验证了决策方法和算法的可行性、有效性与实际可操作性。

As a new type of retail business,smart vending machines(SVM)have been used in many static scenes.Replenishment is limited by time and space,which makes it difficult to apply SVM in dynamic scene(such as high-speed rail scenario),whichposes new challenges to the supply chain scheduling optimization.Based on the above findings,our paper discusses the demand characteristics of the high-speed railway scenario,combines the characteristics of special scenarios with supply chain scheduling,and establishes a new commodity evaluation system and replenishment mechanism adapted to the characteristics of the scenario.And this paper puts forwards an optimization model with the special requirements of the scene as the optimization objective.And the feasibility,effectiveness and practicability of the decision method and algorithm are verified by numerical examples.