A unified framework for stochastic optimization
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Publication:1719609
DOI10.1016/j.ejor.2018.07.014zbMath1430.90445OpenAlexW2884675571WikidataQ129457127 ScholiaQ129457127MaRDI QIDQ1719609
Publication date: 11 February 2019
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ejor.2018.07.014
stochastic programmingdynamic programmingreinforcement learningrobust optimizationbandit problemssimulation optimization
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Cites Work
- Developing real option game models
- Optimal control policies for ambulance diversion
- Optimal technology adoption when the arrival rate of new technologies changes
- A robust optimization approach to energy and reserve dispatch in electricity markets
- Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition
- Scenario-based model predictive control for multi-echelon supply chain management
- An empirical analysis of scenario generation methods for stochastic optimization
- Dynamic sampling algorithms for multi-stage stochastic programs with risk aversion
- Evaluating policies in risk-averse multi-stage stochastic programming
- Analysis of stochastic dual dynamic programming method
- Optimal learning for sequential sampling with non-parametric beliefs
- Optimal learning with a local parametric belief model
- Adaptive stepsizes for recursive estimation with applications in approximate dynamic programming
- On the pricing of American options
- Scenario tree modeling for multistage stochastic programs
- Dynamic portfolio optimization with risk control for absolute deviation model
- Dynamic pickup and delivery problems
- Asymptotically efficient adaptive allocation rules
- Optimal stopping times for detecting changes in distributions
- Stochastic optimal control. The discrete time case
- Multi-stage stochastic optimization applied to energy planning
- Stochastic approximation methods for constrained and unconstrained systems
- Efficient global optimization of expensive black-box functions
- Interpolation of spatial data. Some theory for kriging
- Asynchronous stochastic approximation and Q-learning
- Cut sharing for multistage stochastic linear programs with interstage dependency
- Scenario reduction in stochastic programming
- Online algorithms: a survey
- Regression and Kriging metamodels with their experimental designs in simulation: a review
- Rollout algorithms for stochastic scheduling problems
- A taxonomy of global optimization methods based on response surfaces
- Minimax and risk averse multistage stochastic programming
- Renewable energy investments under different support schemes: a real options approach
- Scenario decomposition of risk-averse multistage stochastic programming problems
- Representation results for law invariant time consistent functions
- Handbook of functional equations. Stability theory
- Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty
- Risk neutral and risk averse stochastic dual dynamic programming method
- A review of dynamic vehicle routing problems
- Recent advances in robust optimization: an overview
- Interrelating operational and financial performance measurements in inventory control
- Model predictive control. With a foreword by M. J. Grimble and M. A. Johnson
- Assessing solution quality in stochastic programs
- Dynamic programming and suboptimal control: a survey from ADP to MPC
- Robust multiobjective optimization \& applications in portfolio optimization
- Introduction to stochastic control theory
- A survey of algorithmic methods for partially observed Markov decision processes
- Stochastic simulation: Algorithms and analysis
- Applying Experimental Design and Regression Splines to High-Dimensional Continuous-State Stochastic Dynamic Programming
- Linear Programming under Uncertainty
- The Allocation of Aircraft to Routes—An Example of Linear Programming Under Uncertain Demand
- The Sample Average Approximation Method for Stochastic Discrete Optimization
- Fully Sequential Procedures for Large-Scale Ranking-and-Selection Problems in Parallel Computing Environments
- General Bounds and Finite-Time Improvement for the Kiefer-Wolfowitz Stochastic Approximation Algorithm
- Modeling with Stochastic Programming
- A Distributional Interpretation of Robust Optimization
- Feature Article: Optimization for simulation: Theory vs. Practice
- Dynamic-Programming Approximations for Stochastic Time-Staged Integer Multicommodity-Flow Problems
- The Knowledge-Gradient Policy for Correlated Normal Beliefs
- Sequential Sampling to Myopically Maximize the Expected Value of Information
- Distributionally Robust Convex Optimization
- Optimal Learning in Experimental Design Using the Knowledge Gradient Policy with Application to Characterizing Nanoemulsion Stability
- Introduction to Uncertainty Quantification
- On the Convergence Rates of Expected Improvement Methods
- Introduction to Stochastic Programming
- Probability and Stochastics
- Multi‐Armed Bandit Allocation Indices
- Approximate Dynamic Programming
- Distributionally Robust Optimization and Its Tractable Approximations
- Stochastic Kriging for Simulation Metamodeling
- A Sequential Sampling Procedure for Stochastic Programming
- Accelerated Stochastic Approximation
- Functional Approximations and Dynamic Programming
- Scenarios and Policy Aggregation in Optimization Under Uncertainty
- Discrete Optimization via Simulation Using COMPASS
- A Robust Optimization Approach to Inventory Theory
- A Knowledge-Gradient Policy for Sequential Information Collection
- On the Best 2-CUSUM Stopping Rule for Quickest Detection of Two-Sided Alternatives in a Brownian Motion Model
- Algorithms for Reinforcement Learning
- The Price of Robustness
- stochastic quasigradient methods and their application to system optimization†
- Optimal maintenance models for systems subject to failure–A Review
- Stochastic Decomposition: An Algorithm for Two-Stage Linear Programs with Recourse
- The Optimal Control of Partially Observable Markov Processes over the Infinite Horizon: Discounted Costs
- On the Convergence of Stochastic Iterative Dynamic Programming Algorithms
- The Optimal Control of Partially Observable Markov Processes over a Finite Horizon
- Introduction to Stochastic Search and Optimization
- Efficient Ranking and Selection in Parallel Computing Environments
- Convergence Analysis of Stochastic Algorithms
- Optimal Starting Times for End-of-Season Sales and Optimal Stopping Times for Promotional Fares
- A lower bound for the correct subset-selection probability and its application to discrete-event system simulations
- Multistage Stochastic Decomposition: A Bridge between Stochastic Programming and Approximate Dynamic Programming
- On Solving Multistage Stochastic Programs with Coherent Risk Measures
- From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning
- Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures
- On the Convergence of Decomposition Methods for Multistage Stochastic Convex Programs
- Learning to Optimize via Posterior Sampling
- Approximate Dynamic Programming
- A Hierarchy of Near-Optimal Policies for Multistage Adaptive Optimization
- Parallel Nonstationary Direct Policy Search for Risk-Averse Stochastic Optimization
- Optimization of Convex Risk Functions
- Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
- L-Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming
- Learning Algorithms for Separable Approximations of Discrete Stochastic Optimization Problems
- Polynomial Approximation--A New Computational Technique in Dynamic Programming: Allocation Processes
- On the Stochastic Approximation Method of Robbins and Monro
- A Stochastic Approximation Method
- Multidimensional Stochastic Approximation Methods
- The theory of dynamic programming
- The origins of kriging
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