Adaptive Ordering and Pricing for Perishable Products

We consider the combined problem of pricing and ordering for a perishable product with unknown demand distribution and censored demand observations resulting from lost sales, faced by a monopolistic retailer. We develop an adaptive pricing and ordering policy with the asymptotic property that the average realized profit per period converges with probability one to the optimal value under complete information on the distribution. The pricing mechanism is modeled as a multiarmed bandit problem, while the order quantity decision, made after the price level is established, is based on a stochastic approximation procedure with multiplicative updates.