关键词: 新零售, 无人零售终端, 遗传算法, 高铁场景

Abstract: 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.

Key words: new retailing, smart vending machine, GA, high-speed rail scenario