Information Relaxations, Duality, and Convex Stochastic Dynamic Programs

DOI10.1287/opre.2014.1322zbMath1327.90149OpenAlexW2154463167MaRDI QIDQ2941432

James E. Smith, David B. Brown

Publication date: 28 August 2015

Published in: Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1287/opre.2014.1322

zbMATH Keywords

dynamic programmingnetwork revenue managementinformation relaxationslost-sales inventory models

Mathematics Subject Classification ID

Stochastic programming (90C15) Dynamic programming (90C39)

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Technical Note—Product-Based Approximate Linear Programs for Network Revenue Management ⋮ Simple explicit formula for near-optimal stochastic lifestyling ⋮ Dynamic Learning and Decision Making via Basis Weight Vectors ⋮ Approximations to Stochastic Dynamic Programs via Information Relaxation Duality ⋮ An Approximation Algorithm for Network Revenue Management Under Nonstationary Arrivals ⋮ Optimistic Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds ⋮ A Subgradient Method Based on Gradient Sampling for Solving Convex Optimization Problems ⋮ Numerical solutions to dynamic portfolio problems with upper bounds ⋮ Merchant Commodity Storage Practice Revisited ⋮ Tax-Aware Dynamic Asset Allocation

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