Journal ArticleDOI
Improved Inventory Targets in the Presence of Limited Historical Demand Data
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TLDR
This paper considers a repeated newsvendor setting where this is not the case and studies the problem of setting inventory targets when there is a limited amount of historical demand data, to quantify the inaccuracy in the inventory-target estimation as a function of the length of the historicalDemand data, the critical fractile, and the shape parameters of the demand distribution.Abstract:
Most of the literature on inventory management assumes that the demand distribution and the values of its parameters are known with certainty. In this paper, we consider a repeated newsvendor setting where this is not the case and study the problem of setting inventory targets when there is a limited amount of historical demand data. Consequently, we achieve the following objectives: (1) to quantify the inaccuracy in the inventory-target estimation as a function of the length of the historical demand data, the critical fractile, and the shape parameters of the demand distribution; and (2) to determine the inventory target that minimizes the expected cost and accounts for the uncertainty around the demand parameters estimated from limited historical data. We achieve these objectives by using the concept of expected total operating cost and representing the demand distribution with the highly flexible Johnson translation system. Our procedures require no restrictive assumptions about the first four moments of the demand random variables, and they can be easily implemented in practical settings with reduced expected total operating costs.read more
Citations
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Journal ArticleDOI
The Data-Driven Newsvendor Problem: New Bounds and Insights
TL;DR: This paper analyzes the sample average approximation SAA approach for the data-driven newsvendor problem and obtains a new analytical bound on the probability that the relative regret of the SAA solution exceeds a threshold.
Journal ArticleDOI
On the calculation of safety stocks when demand is forecasted
TL;DR: Correct lead time demand variance expressions and reorder levels for inventory systems with a constant lead time where demand fluctuates around a constant level are presented.
Journal ArticleDOI
Confidence-based optimisation for the newsvendor problem under binomial, Poisson and exponential demand
TL;DR: In this paper, the authors propose a strategy to address the issue of demand estimation in single-item single-period stochastic inventory optimisation problems, where the decision maker is given a set of past demand samples and employs confidence interval analysis in order to identify a range of candidate order quantities that, with prescribed confidence probability, includes the real optimal order quantity for the underlying Stochastic demand process with unknown stationary parameter(s).
Journal ArticleDOI
Stochastic simulation under input uncertainty: A Review
Canan G. Corlu,Alp Akcay,Wei Xie +2 more
TL;DR: The goal of this paper is to present input uncertainty research in stochastic simulations by providing a classification of major research streams and focusing on the new developments in recent years, as well as reviewing application papers that investigate the value of representing input uncertainty in the simulation of real-world Stochastic systems in various industries.
Journal ArticleDOI
Prescriptive Analytics for Flexible Capacity Management
Pascal M. Notz,Richard Pibernik +1 more
TL;DR: The universal approximation property for the kernelized ERM approach when using a universal (data-independent) kernel is proved and how out-of-sample guarantees can be derived for various kernels are shown.
References
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Book
Convex Optimization
Stephen Boyd,Lieven Vandenberghe +1 more
TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Journal ArticleDOI
Numerical Recipes, The Art of Scientific Computing
Book
Simulation Modeling and Analysis
Averill M. Law,W. David Kelton +1 more
TL;DR: The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering, business, computer science and operations research.
Book
Numerical Recipes 3rd Edition: The Art of Scientific Computing
TL;DR: This new edition incorporates more than 400 Numerical Recipes routines, many of them new or upgraded, and adopts an object-oriented style particularly suited to scientific applications.