Online Network Revenue Management Using Thompson Sampling
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Publication:5131540
DOI10.1287/opre.2018.1755zbMath1446.90095OpenAlexW3122960105MaRDI QIDQ5131540
He Wang, Kris Johnson Ferreira, David Simchi-Levi
Publication date: 8 November 2020
Published in: Operations Research (Search for Journal in Brave)
Full work available at URL: https://hdl.handle.net/1721.1/125757
Management decision making, including multiple objectives (90B50) Deterministic network models in operations research (90B10) Microeconomic theory (price theory and economic markets) (91B24)
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Cites Work
- Simple Policies for Dynamic Pricing with Imperfect Forecasts
- Close the Gaps: A Learning-While-Doing Algorithm for Single-Product Revenue Management Problems
- A Re-Solving Heuristic with Bounded Revenue Loss for Network Revenue Management with Customer Choice
- Dynamic Pricing with an Unknown Demand Model: Asymptotically Optimal Semi-Myopic Policies
- Dynamic Pricing for Nonperishable Products with Demand Learning
- Dynamic Pricing Without Knowing the Demand Function: Risk Bounds and Near-Optimal Algorithms
- Dynamic Pricing with a Prior on Market Response
- Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis
- Linearly Parameterized Bandits
- Performance of an LP-Based Control for Revenue Management with Unknown Demand Parameters
- Asymptotic Behavior of an Allocation Policy for Revenue Management
- Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons
- A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management
- Blind Network Revenue Management
- Learning to Optimize via Posterior Sampling
- Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
- On the Asymptotic Behavior of Bayes' Estimates in the Discrete Case
- Finite-time analysis of the multiarmed bandit problem
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