An Inner-Outer Approximation Approach to Chance Constrained Optimization
From MaRDI portal
Publication:5355201
DOI10.1137/15M1049750zbMath1387.90170OpenAlexW2750408863MaRDI QIDQ5355201
Armin Hoffmann, Pu Li, Abebe Geletu, Michael Klöppel
Publication date: 7 September 2017
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/15m1049750
Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Stochastic programming (90C15)
Related Items
Solving joint chance constrained problems using regularization and Benders' decomposition ⋮ A discussion of probability functions and constraints from a variational perspective ⋮ Nonconvex and nonsmooth approaches for affine chance-constrained stochastic programs ⋮ On the algorithmic solution of optimization problems subject to probabilistic/robust (probust) constraints ⋮ Optimization under Rare Chance Constraints ⋮ Chance-constrained optimization under limited distributional information: a review of reformulations based on sampling and distributional robustness ⋮ Approximate methods for solving chance-constrained linear programs in probability measure space ⋮ Joint chance-constrained multi-objective multi-commodity minimum cost network flow problem with copula theory ⋮ Solving Chance-Constrained Problems via a Smooth Sample-Based Nonlinear Approximation ⋮ Optimal Neumann Boundary Control of a Vibrating String with Uncertain Initial Data and Probabilistic Terminal Constraints ⋮ Chance constrained optimization of elliptic PDE systems with a smoothing convex approximation ⋮ Analytic approximation and differentiability of joint chance constraints ⋮ A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Level bundle methods for constrained convex optimization with various oracles
- A smoothing function approach to joint chance-constrained programs
- Convex proximal bundle methods in depth: a unified analysis for inexact oracles
- A characterization of the subdifferential of singular Gaussian distribution functions
- A sampling-and-discarding approach to chance-constrained optimization: feasibility and Optimality
- Scenario reduction in stochastic programming with respect to discrepancy distances
- Implementable algorithm for stochastic optimization using sample average approximations
- A model for dynamic chance constraints in hydro power reservoir management
- Convexity of chance constraints with independent random variables
- Sample average approximation method for chance constrained programming: Theory and applications
- Convex set functions in d-space
- On extensions of the Brunn-Minkowski and Prekopa-Leindler theorems, including inequalities for log concave functions, and with an application to the diffusion equation
- Differentiation formulas for probability functions: The transformation method
- Optimization of a continuous distillation process under random inflow rate.
- Convexity of chance constrained programming problems with respect to a new generalized concavity notion
- Uncertain convex programs: randomized solutions and confidence levels
- Derivatives of probability functions and some applications
- On safe tractable approximations of chance constraints
- Value-at-risk optimization using the difference of convex algorithm
- Augmented Lagrangian method for probabilistic optimization
- Distributionally robust joint chance constraints with second-order moment information
- Regularization methods for optimization problems with probabilistic constraints
- On distributionally robust chance-constrained linear programs
- Convex relaxations of chance constrained optimization problems
- A sequential convex program method to DC program with joint chance constraints
- Techniques of variational analysis
- Ambiguous chance constrained problems and robust optimization
- Chance-Constrained Programming
- Advances and applications of chance-constrained approaches to systems optimisation under uncertainty
- A Gradient Formula for Linear Chance Constraints Under Gaussian Distribution
- Sequential Convex Approximations to Joint Chance Constrained Programs: A Monte Carlo Approach
- Theory and Applications of Robust Optimization
- Stochastic programming problems with generalized integrated chance constraints
- On Safe Tractable Approximations of Chance-Constrained Linear Matrix Inequalities
- A difference of convex formulation of value-at-risk constrained optimization
- A Sample Approximation Approach for Optimization with Probabilistic Constraints
- Lectures on Stochastic Programming
- On minimization of a function under an equality chance constraint
- Deterministic approximations of probability inequalities
- A Characterization of Epi-Convergence in Terms of Convergence of Level Sets
- Convexity of Chance Constraints with Dependent Random Variables: The Use of Copulae
- The Minimization of Semicontinuous Functions: Mollifier Subgradients
- Gradient Formulae for Nonlinear Probabilistic Constraints with Gaussian and Gaussian-Like Distributions
- Eventual convexity of chance constrained feasible sets
- (Sub-)Gradient Formulae for Probability Functions of Random Inequality Systems under Gaussian Distribution
- Convex Approximations of Chance Constrained Programs
- Chance-constrained optimal control for multireservoir system optimization and risk analysis
- Distributionally robust chance constraints for non-linear uncertainties
