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Parallel processors for planning under uncertainty
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Numerical Techniques for Stochastic Optimization
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Stochastic Quasigradient Methods and their Implementation
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Approximation Techniques in Stochastic Programming
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Optimal Investments for Electricity Generation: A Stochastic Model and a Test-Problem
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Large Scale Linear Programming Techniques
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Multidimensional Integration and Stochastic Programming
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Partitioning procedures for solving mixed-variables programming problems
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Nested decomposition for dynamic models
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Sublinear upper bounds for stochastic programs with recourse
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Solving staircase linear programs by the simplex method, 1: Inversion
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An advanced implementation of the Dantzig—Wolfe decomposition algorithm for linear programming
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Decomposition of linear programs using parallel computation
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Planning under uncertainty using parallel computing
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A new polynomial-time algorithm for linear programming
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Aggregation bounds in stochastic linear programming
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Revised dantzig-wolfe decomposition for staircase-structured linear programs
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Solving staircase linear programs by the simplex method, 2: Pricing
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Multidimensional numerical integration using pseudorandom numbers
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A tight upper bound for the expectation of a convex function of a multivariate random variable
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Designing approximation schemes for stochastic optimization problems, in particular for stochastic programs with recourse
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A first order approach to a class of multi-time-period stochastic programming problems
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Algorithms for stochastic programs: The case of nonstochastic tenders
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Multistage stochastic programs with block-separable recourse
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A variational-like inequality for multifunctions with applications
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The decomposition principle for linear programs
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Solving Stochastic Programming Problems with Recourse Including Error Bounds
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stochastic quasigradient methods and their application to system optimization †
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Epi‐consistency of convex stochastic programs
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A basis factorization method for multi-stage linear programming problems with an application to optimal operation of an energy plant
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Stochastic Programming
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On Minimizing a Convex Function Subject to Linear Inequalities
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Programming Under Uncertainty: The Equivalent Convex Program
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L -Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming
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Programming under Uncertainty and Stochastic Optimal Control
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Stability in Two-Stage Stochastic Programming
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A Separable Piecewise Linear Upper Bound for Stochastic Linear Programs
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On the Asymptotic Theory of Fixed-Width Sequential Confidence Intervals for the Mean
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Bounds on the Expectation of a Convex Function of a Multivariate Random Variable
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Asymptotic Behavior of Statistical Estimators and of Optimal Solutions of Stochastic Optimization Problems
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Linear Programming under Uncertainty
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Linear Programming Under Uncertainty
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Nested Decomposition and Multi-Stage Linear Programs
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A Perspective on the Use of Control Variables to Increase the Efficiency of Monte Carlo Simulations
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Importance Sampling for Stochastic Simulations
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On the Convergence in Distribution of Measurable Multifunctions (Random Sets) Normal Integrands, Stochastic Processes and Stochastic Infima
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Computing Bounds for Stochastic Programming Problems by Means of a Generalized Moment Problem
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Scenarios and Policy Aggregation in Optimization Under Uncertainty
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Probabilistic Models for Linear Programming
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Bounds on the Expectation of a Convex Function of a Random Variable: With Applications to Stochastic Programming
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Efficiency of Multivariate Control Variates in Monte Carlo Simulation
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Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs
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Decomposition Principle for Linear Programs
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Linear Programming and Extensions
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23. A Decomposition Principle for Linear Programs
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On Projected Newton Barrier Methods for Linear Programming and an Equivalence to Karmarkar's Projective Method.
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Importance Sampling for Stochastic Simulations.
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A Parallel Decomposition Algorithm for Staircase Linear Programs
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The Parallel of Decomposition of Linear Programs
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Stopping Rules for a Class of Sampling-Based Stochastic Programming Algorithms
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Random Yield and Random Demand in a Production System with Downward Substitution
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Restricted-Recourse Bounds for Stochastic Linear Programming
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A Hybrid Monte Carlo Local Branching Algorithm for the Single Vehicle Routing Problem with Stochastic Demands
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Volumetric center method for stochastic convex programs using sampling
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On Rates of Convergence for Stochastic Optimization Problems Under Non-I.I.D. Sampling
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Capacity Expansion Problem by Monte Carlo Sampling Method
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The Parallel of Decomposition of Linear Programs
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Importance sampling for stochastic programming
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Scenario reduction heuristics for a rolling stochastic programming simulation of bulk energy flows with uncertain fuel costs
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Effects of fuel cost uncertainty on optimal energy flows in U.S.
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Four essays on allocation problems in supply chain management
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