Learning with Posterior Sampling for Revenue Management under Time-varying Demand

arXiv:2405.04910v1 Announce Type: new
Abstract: This paper discusses the revenue management (RM) problem to maximize revenue by pricing items or services. One challenge in this problem is that the demand distribution is unknown and varies over time in real applications such as airline and retail industries. In particular, the time-varying demand has not been well studied under scenarios of unknown demand due to the difficulty of jointly managing the remaining inventory and estimating the demand. To tackle this challenge, we …

abstract airline applications arxiv challenge cs.lg demand distribution industries management paper posterior pricing retail revenue sampling services stat.ml type