Optimality functions in stochastic programming
From MaRDI portal
Publication:715095
DOI10.1007/s10107-011-0453-3zbMath1267.90090OpenAlexW1987609385WikidataQ105583396 ScholiaQ105583396MaRDI QIDQ715095
Publication date: 15 October 2012
Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10107-011-0453-3
Nonconvex programming, global optimization (90C26) Optimality conditions and duality in mathematical programming (90C46) Stochastic programming (90C15)
Related Items
Optimality functions and lopsided convergence ⋮ On sample size control in sample average approximations for solving smooth stochastic programs ⋮ Sample average approximation with heavier tails. I: Non-asymptotic bounds with weak assumptions and stochastic constraints ⋮ Consistent approximations in composite optimization ⋮ Approximations of semicontinuous functions with applications to stochastic optimization and statistical estimation ⋮ Two stochastic optimization algorithms for convex optimization with fixed point constraints ⋮ Spectral projected gradient method for stochastic optimization ⋮ Variance reduction for sequential sampling in stochastic programming ⋮ Inexact Restoration approach for minimization with inexact evaluation of the objective function ⋮ Iteration and evaluation complexity for the minimization of functions whose computation is intrinsically inexact ⋮ Asymptotic Results of Stochastic Decomposition for Two-Stage Stochastic Quadratic Programming ⋮ Nonmonotone line search methods with variable sample size ⋮ Variational Theory for Optimization under Stochastic Ambiguity ⋮ Solving Nonsmooth and Nonconvex Compound Stochastic Programs with Applications to Risk Measure Minimization
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On solving large-scale finite minimax problems using exponential smoothing
- Uniform laws of large numbers for set-valued mappings and subdifferentials of random functions
- An adaptive Monte Carlo algorithm for computing mixed logit estimators
- Efficient sample sizes in stochastic nonlinear programming
- Sample average approximation of expected value constrained stochastic programs
- A smoothing method for solving portfolio optimization with CVaR and applications in allocation of generation asset
- Smooth sample average approximation of stationary points in nonsmooth stochastic optimization and applications
- Statistical testing of optimality conditions in multiresponse simulation-based optimization
- Statistical verification of optimality conditions for stochastic programs with recourse
- A simulation-based approach to two-stage stochastic programming with recourse
- A branch and bound method for stochastic global optimization
- Monte Carlo bounding techniques for determinig solution quality in stochastic programs
- On the use of consistent approximations in the solution of semi-infinite optimization and optimal control problems
- Duality and statistical tests of optimality for two stage stochastic programs
- Optimization. Algorithms and consistent approximations
- Sample-path solution of stochastic variational inequalities
- Nonlinear stochastic programming by Monte-Carlo estimators
- Stochastic linear programming. Models, theory, and computation
- Extensions of stochastic optimization results to problems with system failure probability functions
- Convergence theory for nonconvex stochastic programming with an application to mixed logit
- Stochastic decomposition. A statistical method for large scale stochastic linear programming
- On Choosing Parameters in Retrospective-Approximation Algorithms for Stochastic Root Finding and Simulation Optimization
- Finding Optimal Material Release Times Using Simulation-Based Optimization
- A Sequential Sampling Procedure for Stochastic Programming
- A Sample Approximation Approach for Optimization with Probabilistic Constraints
- Lectures on Stochastic Programming
- Robust Stochastic Approximation Approach to Stochastic Programming
- Asymptotic Behavior of Optimal Solutions in Stochastic Programming
- Introduction to Stochastic Search and Optimization
- Convex Approximations of Chance Constrained Programs
