A Nonparametric Asymptotic Analysis of Inventory Planning with Censored Demand

Authors:
Woonghee Tim Huh;Paat Rusmevichientong
Affiliations:
Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027;School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Venue:
Mathematics of Operations Research
Year:
2009

Citing 17
Cited 6

Myopic policies for some inventory models with uncertain demand distributions

Management Science
Informational dynamics of censored observations

Management Science
Finite-time Analysis of the Multiarmed Bandit Problem

Machine Learning
Stalking Information: Bayesian Inventory Management with Unobserved Lost Sales

Management Science
Adaptive Ordering and Pricing for Perishable Products

Operations Research
The Censored Newsvendor and the Optimal Acquisition of Information

Operations Research
An Adaptive, Distribution-Free Algorithm for the Newsvendor Problem with Censored Demands, with Applications to Inventory and Distribution

Management Science
Inventory Control in Directed Networks: A Note on Linear Costs

Operations Research
Learning Algorithms for Separable Approximations of Discrete Stochastic Optimization Problems

Mathematics of Operations Research
Online convex optimization in the bandit setting: gradient descent without a gradient

SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Provably Near-Optimal Sampling-Based Policies for Stochastic Inventory Control Models

Mathematics of Operations Research
Dynamic Inventory Management with Learning About the Demand Distribution and Substitution Probability

Manufacturing & Service Operations Management
Regret in the Newsvendor Model with Partial Information

Operations Research
Analysis of Perishable-Inventory Systems with Censored Demand Data

Operations Research
Logarithmic regret algorithms for online convex optimization

COLT'06 Proceedings of the 19th annual conference on Learning Theory
Solving operational statistics via a Bayesian analysis

Operations Research Letters
A practical inventory control policy using operational statistics

Operations Research Letters

An Adaptive Algorithm for Finding the Optimal Base-Stock Policy in Lost Sales Inventory Systems with Censored Demand

Mathematics of Operations Research
Robust Controls for Network Revenue Management

Manufacturing & Service Operations Management
Fully Distribution-Free Profit Maximization: The Inventory Management Case

Mathematics of Operations Research
Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator

Operations Research
Weak aggregating algorithm for the distribution-free perishable inventory problem

Operations Research Letters
Online lot-sizing problems with ordering, holding and shortage costs

Operations Research Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

We study stochastic inventory planning with lost sales and instantaneous replenishment where, contrary to the classical inventory theory, knowledge of the demand distribution is not available. Furthermore, we observe only the sales quantity in each period and lost sales are unobservable, that is, demand data are censored. The manager must make an ordering decision in each period based only on historical sales data. Excess inventory is either perishable or carried over to the next period. In this setting, we propose nonparametric adaptive policies that generate ordering decisions over time. We show that the T-period average expected cost of our policy differs from the benchmark newsvendor cost---the minimum expected cost that would have incurred if the manager had known the underlying demand distribution---by at most O(1/T0.5).