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

نویسندگان

  • Woonghee Tim Huh
  • Retsef Levi
  • Paat Rusmevichientong
  • James B. Orlin
چکیده

Using the well-known product-limit form of the Kaplan-Meier estimator from statistics, we propose a new class of nonparametric adaptive data-driven policies for stochastic inventory control problems. We focus on the distribution-free newsvendor model with censored demands. The assumption is that the demand distribution is not known and there are only sales data available. We study the theoretical performance of the new policies and show that for discrete demand distributions they converge almost surely to the set of optimal solutions. Computational experiments suggest that the new policies converge for general demand distributions, not necessarily discrete, and demonstrate that they are significantly more robust than previously known policies. As a by-product of the theoretical analysis, we obtain new results on the asymptotic consistency of the Kaplan-Meier estimator for discrete random variables that extend existing work in statistics. To the best of our knowledge, this is the first application of the Kaplan-Meier estimator within an adaptive optimization algorithm, in particular, the first application to stochastic inventory control models. We believe that this work will lead to additional applications in other domains.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

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

Adaptive Data-Driven Inventory Control Policies Based on Kaplan-Meier Estimator for Censored Demand Woonghee Tim Huh Sauder School of Business, University of British Columbia, Vancouver, BC, Canada, V6T 1Z2. [email protected] Retsef Levi Sloan School of Management, MIT, Cambridge, MA, 02139 USA [email protected] Paat Rusmevichientong School of Operations Research and Information Engineering, C...

متن کامل

Adaptive Data-Driven Inventory Control Policies Based on Kaplan-Meier Estimator

Adaptive Data-Driven Inventory Control Policies Based on Kaplan-Meier Estimator Woonghee Tim Huh Sauder School of Business, University of British Columbia, Vancouver, BC, Canada, V6T 1Z2. [email protected] Retsef Levi Sloan School of Management, MIT, Cambridge, MA, 02139 USA [email protected] Paat Rusmevichientong School of Operations Research and Information Engineering, Cornell University, I...

متن کامل

Nonparametric Demand Forecasting with Right Censored Observations

In a newsvendor inventory system, demand observations often get right censored when there are lost sales and no backordering. Demands for newsvendor-type products are often forecasted from censored observations. The Kaplan-Meier product limit estimator is the well-known nonparametric method to deal with censored data, but it is undefined beyond the largest observation if it is censored. To addr...

متن کامل

Testing Censoring Point Independence

Identification in censored regression analysis and hazard models of duration outcomes relies on the condition that censoring points are independent of latent outcomes, an assumption which may be questionable in many settings. This note proposes a test for this assumption based on a Kolmogorov-Smirnov-like test statistic comparing two different nonparametric estimators for the latent outcome cdf...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Operations Research

دوره 59  شماره 

صفحات  -

تاریخ انتشار 2011