Optimal Learning Algorithms for Stochastic Inventory Systems with Random Capacities
Author:
Affiliation:
1. Industrial and Operations Engineering University of Michigan Ann Arbor MI48109 USA
2. Technology and Operations, Ross School of Business University of Michigan Ann Arbor MI48109 USA
Publisher
Wiley
Subject
Management of Technology and Innovation,Industrial and Manufacturing Engineering,Management Science and Operations Research
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/poms.13178
Reference57 articles.
1. Agrawal S. R.Jia.2019.Learning in Structured MDPS with Convex Cost Functions: Improved Regret Bounds for Inventory Management. Proceedings of the 2019 ACM Conference on Economics and Computation EC ’19 : ACM New York NY USA pp. 743–744.
2. Simultaneous Capacity and Production Management of Short-Life-Cycle, Produce-to-Stock Goods Under Stochastic Demand
3. Looking Upstream: Optimal Policies for a Class of Capacitated Multi-Stage Inventory Systems
4. Stochastic Inventory Models with Limited Production Capacity and Periodically Varying Parameters
5. Ban G. Y.2020.Confidence intervals for data‐driven inventory policies with demand censoring.Working paper London Business School London UK.
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