The topic of dynamic pricing and learning has received a considerable amount of attention
in recent years, from different scientific communities. We survey these literature streams: we …

Dynamic pricing enables a firm to increase revenue by better matching supply with demand,
responding to shifting demand patterns, and achieving customer segmentation. In the last 20 …

The contextual bandit literature has traditionally focused on algorithms that address the
exploration–exploitation tradeoff. In particular, greedy algorithms that exploit current …

As a novel trading mode, the peer-to-peer (P2P) energy market cannot be accepted by the
end-users immediately. There is an adoption process before all the energy prosumers …

We consider a firm that sells products over $ T $ periods without knowing the demand
function. The firm sequentially sets prices to earn revenue and to learn the underlying …

We consider a logit model-based framework for modeling joint pricing and assortment
decisions that take into account customer features. This model provides a significant …

We consider a retailer selling a single product with limited on-hand inventory over a finite
selling season. Customer demand arrives according to a Poisson process, the rate of which …

Revenue management (RM) is essential for a wide range of industries such as airlines,
hotels, cruise lines, fashion, and seasonal retail. This paper focuses on the multi-perishable …

We consider a joint pricing and inventory control problem in which the customer's response
to selling price and the demand distribution are not known a priori. Unsatisfied demand is …

We consider a seller's dynamic pricing problem with demand learning and reference effects.
We first study the case in which customers are loss-averse: they have a reference price that …