[HTML][HTML] Inventory–forecasting: Mind the gap
We are concerned with the interaction and integration between demand forecasting and
inventory control, in the context of supply chain operations. The majority of the literature is …
inventory control, in the context of supply chain operations. The majority of the literature is …
Data‐driven research in retail operations—A review
We review the operations research/management science literature on data‐driven methods
in retail operations. This line of work has grown rapidly in recent years, thanks to the …
in retail operations. This line of work has grown rapidly in recent years, thanks to the …
Marrying stochastic gradient descent with bandits: Learning algorithms for inventory systems with fixed costs
We consider a periodic-review single-product inventory system with fixed cost under
censored demand. Under full demand distributional information, it is well known that the …
censored demand. Under full demand distributional information, it is well known that the …
Adaptive inventory replenishment using structured reinforcement learning by exploiting a policy structure
We consider an inventory replenishment problem with unknown and non-stationary
demand. We design a structured reinforcement learning algorithm that efficiently adapts the …
demand. We design a structured reinforcement learning algorithm that efficiently adapts the …
A decision integration strategy for short-term demand forecasting and ordering for red blood cell components
Blood transfusion is one of the most crucial and commonly administered therapeutics
worldwide. The need for more accurate and efficient ways to manage blood demand and …
worldwide. The need for more accurate and efficient ways to manage blood demand and …
Closing the gap: A learning algorithm for lost-sales inventory systems with lead times
We consider a periodic-review, single-product inventory system with lost sales and positive
lead times under censored demand. In contrast to the classical inventory literature, we …
lead times under censored demand. In contrast to the classical inventory literature, we …
Nonparametric learning algorithms for joint pricing and inventory control with lost sales and censored demand
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 …
to selling price and the demand distribution are not known a priori. Unsatisfied demand is …
Perishable inventory systems: Convexity results for base-stock policies and learning algorithms under censored demand
We develop the first nonparametric learning algorithm for periodic-review perishable
inventory systems. In contrast to the classical perishable inventory literature, we assume that …
inventory systems. In contrast to the classical perishable inventory literature, we assume that …
[HTML][HTML] Big data driven order-up-to level model: Application of machine learning
JBB Clausen, H Li - Computers & Operations Research, 2022 - Elsevier
Data driven optimisation has become one of the research frontiers in operations
management and operations research. Likewise, the recent academic interest in big data …
management and operations research. Likewise, the recent academic interest in big data …
A distributionally robust optimization approach for multi-product inventory decisions with budget constraint and demand and yield uncertainties
This study develops a distributionally robust optimization approach for inventory decisions
for a retailer with limited budget ordering multiple products from multiple suppliers. The …
for a retailer with limited budget ordering multiple products from multiple suppliers. The …