Abstract
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.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call