This study explores an inventory replenishment problem for an omnichannel retailer selling a product with demand uncertainties and service level requirements in different channels through a capacity-sharing strategy. The omnichannel retailer allows customers to order products online and then pick them up in retail stores. The capacity-sharing strategy is considered to reduce travel costs when the omnichannel retailer delivers products in different channels. With the capacity-sharing strategy, some products can be transferred from the online delivery vehicle to the retail store delivery vehicle. The expectation and the bounds on the online route travel cost of the capacity-sharing strategy are determined, based on which the capacity-sharing rules are established. Optimization models and a solution procedure are developed to solve the omnichannel retailer inventory replenishment problem. To ensure adequate performance, service level requirements are considered when making delivery decisions. Numerical experiments using randomly generated and artificial instances are performed to verify the effectiveness and practicality of the proposed optimization models and the solution procedure. The results show that the proposed models and solution procedure can effectively reduce travel costs, and can provide effective schedule and delivery quantity decision support for omnichannel retailers.

中文翻译：

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在需求不确定性和服务水平要求的情况下，利用车辆容量共享优化全渠道零售商库存补给


本研究探讨了全渠道零售商通过容量共享策略在不同渠道销售具有需求不确定性和服务水平要求的产品的库存补货问题。全渠道零售商允许客户在线订购产品，然后在零售店提货。当全渠道零售商在不同渠道交付产品时，容量共享策略被认为可以降低差旅成本。通过运力共享策略，一些产品可以从在线配送车辆转移到零售商店配送车辆。确定了运力共享策略在线路线出行成本的期望和界限，并在此基础上建立了运力共享规则。开发优化模型和解决程序来解决全渠道零售商库存补货问题。为了确保足够的性能，在做出交付决策时会考虑服务水平要求。使用随机生成和人工实例进行数值实验，以验证所提出的优化模型和求解过程的有效性和实用性。结果表明，所提出的模型和解决方案可以有效降低差旅成本，并能为全渠道零售商提供有效的时间表和交货数量决策支持。