第三方仓库作为服务提供商, 主要以期望收益最大化为目标, 但是必须满足一定的顾客服务标准。针对高需求环境, 考虑顾客服务水平约束, 提出了一个基于排队论的随机设计优化模型以使仓库的期望收益最大化。采用动态优化算法对模型求解, 选取实例进行了数值实验。结果显示, 模型的优化设计显著地提高了高需求环境下该第三方仓库的期望收益。在此基础上, 找到了服务约束的可行范围和有效范围, 为决策者制定服务标准提供了依据。
As service providers, third-party warehouses mainly focus on increasing the expected revenue, but at the same time have to meet certain service standards. In a high demand environment, a stochastic design model based on queuing theory and taken into account of service constraint is preserted. The objective of the model is to maximize the expected long-run revenue. The problem is solved by dynamic programming and numerical experiments are conducted by using real data in a third-party warehouse. Finally, the results show that the new design in our method can improve the expected revenue of public storage warehouses with high demand and service constraints rate. Based on the result, the feasible and effective ranges of the service factor for decision-makers are further identified.
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