Technical Note—Revenue Management with Calendar-Aware and Dependent Demands: Asymptotically Tight Fluid Approximations
提出能同时容纳大需求量和强波动性、且允许非重叠时段需求依赖的模型，并给出可高效计算且有性能保证的策略，对收益管理研究者有用。
Revenue Management with Dependent Demands In the revenue management literature, a standard approach to model the demand is based on dividing the selling horizon into a number of small time periods such that there is at most one customer arrival at each time period and that the customer arrivals at different time periods are independent of each other. Under this demand model, if the mean demand for a product increases with rate T, then the standard deviation of the demand must increase with rate square root of T. In other words, large demand volume and large demand variability cannot coexist. In “Technical Note—Revenue Management with Calendar-Aware and Dependent Demands: Asymptotically Tight Fluid Approximations,” Li, Rusmevichientong, and Topaloglu consider demand models that can simultaneously incorporate large demand volume and large demand variability while also allowing dependence between the demands over nonoverlapping time intervals. Under such demand models, they give efficiently computable policies that admit performance guarantees.