Demand Estimation from Censored Observations with Inventory Record Inaccuracy

@article{Mersereau2015DemandEF,
  title={Demand Estimation from Censored Observations with Inventory Record Inaccuracy},
  author={Adam J. Mersereau},
  journal={Manuf. Serv. Oper. Manag.},
  year={2015},
  volume={17},
  pages={335-349}
}
A retailer cannot sell more than it has in stock; therefore, its sales observations are a censored representation of the underlying demand process. When a retailer forecasts demand based on past sales observations, it requires an estimation approach that accounts for this censoring. Several authors have analyzed inventory management with demand learning in environments with censored observations, but the authors assume that inventory levels are known and hence that stockouts are observed… 

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References

SHOWING 1-10 OF 47 REFERENCES

Information-Sensitive Replenishment when Inventory Records Are Inaccurate

A periodic review inventory system with imperfect inventory records and unobserved lost sales is considered, and it is found that the myopic heuristic is likely sufficiently good in practical settings targeting high service levels.

A Nonparametric Asymptotic Analysis of Inventory Planning with Censored Demand

Stochastic inventory planning with lost sales and instantaneous replenishment where knowledge of the demand distribution is not available is studied and nonparametric adaptive policies that generate ordering decisions over time are proposed.

Stalking Information: Bayesian Inventory Management with Unobserved Lost Sales

Retailers are frequently uncertain about the underlying demand distribution of a new product. When taking the empirical Bayesian approach of Scarf 1959, they simultaneously stock the product over

Retail Inventory Management When Records Are Inaccurate

This paper considers an intelligent inventory management tool that accounts for record inaccuracy using a Bayesian belief of the physical inventory level, and shows that a probability distribution on physical inventory levels is a sufficient summary of past sales and replenishment observations and that this probability distribution can be efficiently updated as observations are accumulated.

Demand estimation in lost sales inventory systems

This article considers the problem of estimating parameters of the demand distribution in lost sales inventory systems. In periods when lost sales occur demand is not observed; one knows only that

Bounds and Heuristics for Optimal Bayesian Inventory Control with Unobserved Lost Sales

This paper considers a finite-horizon inventory control problem for a nonperishable product with unobserved lost sales and a demand distribution having an unknown parameter and proposes two heuristics that outperform the myopic policies by a wide margin.

A Censored-Data Multiperiod Inventory Problem with Newsvendor Demand Distributions

It is shown that the Weibull is the only newsvendor distribution for which the optimal solution can be expressed in scalable form and for the special case of exponential demand the cost function is convex, so that for the storable inventory case, the optimal policy can be found using simple one-step look-ahead recursions whereas for the perishable case the optimal Policy can be expression by exact closed-form formulas.

Dynamic Inventory Management with Learning About the Demand Distribution and Substitution Probability

It is proved that with nonperishable inventory, the famous “ stock more” result is often reversed to “stock less,” in that the Bayesian optimal inventory level with unobserved lost sales is lower than the myopic inventory level.

Estimating negative binomial demand for retail inventory management with unobservable lost sales

The importance of effective inventory management has greatly increased for many major retailers because of more intense competition. Retail inventory management methods often use assumptions and

Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator

This work proposes a new class of nonparametric adaptive data-driven policies for stochastic inventory control problems on the distribution-free newsvendor model with censored demands and obtains new results on the asymptotic consistency of the Kaplan-Meier estimator for discrete random variables that extend existing work in statistics.