Data-driven newsvendor problem: Performance of the sample average approximation
We consider the data-driven newsvendor problem in which a manager makes inventory
decisions sequentially and learns the unknown demand distribution based on observed …
decisions sequentially and learns the unknown demand distribution based on observed …
Sample complexity of policy learning for inventory control with censored demand
Traditional offline-learning studies in inventory control assume access to true demand
samples $\{d_n\} _ {n= 1}^{N} $. However, in many applications, true demand samples are …
samples $\{d_n\} _ {n= 1}^{N} $. However, in many applications, true demand samples are …
Sailing through the Dark: Provably Sample-Efficient Inventory Control
We consider the important open problems of 1) What is the sample complexity (ie, how many
data samples are needed) of learning nearly optimal policy for multi-stage stochastic …
data samples are needed) of learning nearly optimal policy for multi-stage stochastic …
A Nonparametric Learning Algorithm for a Stochastic Multi-echelon Inventory Problem
We consider a periodic-review single-product multi-echelon inventory problem with
instantaneous replenishment. In each period, the decision-maker makes ordering decisions …
instantaneous replenishment. In each period, the decision-maker makes ordering decisions …
[图书][B] Single-stage approximations of multi-echelon inventory models
For supply-chain systems with complex network structures, the forms of system-optimal
inventory-control policies are often not known. Even for systems with known optimal policies …
inventory-control policies are often not known. Even for systems with known optimal policies …
Closing the Gaps: Optimality of Sample Average Approximation for Data-Driven Newsvendor Problems
We study the regret performance of Sample Average Approximation (SAA) for data-driven
newsvendor problems with general convex inventory costs. In literature, the optimality of …
newsvendor problems with general convex inventory costs. In literature, the optimality of …