A two-step gradient estimation approach for setting supply chain operating parameters

DOI10.1016/j.cor.2017.12.001zbMath1391.90066OpenAlexW2773345076MaRDI QIDQ1651591

Philip M. Kaminsky, Stewart Liu

Publication date: 12 July 2018

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2017.12.001

zbMATH Keywords

supply chain disruptionretrospective optimizationsample path optimizationstochastic gradient search

Mathematics Subject Classification ID

Stochastic programming (90C15) Transportation, logistics and supply chain management (90B06) Inventory, storage, reservoirs (90B05)

Cites Work

• Unnamed Item
• Construct, Merge, Solve \& Adapt A new general algorithm for combinatorial optimization
• Solving operational statistics via a Bayesian analysis
• Smooth sample average approximation of stationary points in nonsmooth stochastic optimization and applications
• Monte Carlo bounding techniques for determinig solution quality in stochastic programs
• The sample average approximation method applied to stochastic routing problems: a computational study
• A simulation optimization approach for a two-echelon inventory system with service level constraints
• Optimization of (s, S) Inventory Systems with Random Lead Times and a Service Level Constraint
• On Choosing Parameters in Retrospective-Approximation Algorithms for Stochastic Root Finding and Simulation Optimization
• An Adaptive, Distribution-Free Algorithm for the Newsvendor Problem with Censored Demands, with Applications to Inventory and Distribution
• Newsvendor Bounds and Heuristic for Optimal Policies in Serial Supply Chains
• A Nonparametric Asymptotic Analysis of Inventory Planning with Censored Demand
• Computational Issues in an Infinite-Horizon, Multiechelon Inventory Model
• Critical Number Policies for Inventory Models with Periodic Data
• Analysis of Sample-Path Optimization
• Lower Bounds for Multi-Echelon Stochastic Inventory Systems
• In-Process Inventories
• Provably Near-Optimal Sampling-Based Policies for Stochastic Inventory Control Models
• Stochastic Estimation of the Maximum of a Regression Function