A discussion of probability functions and constraints from a variational perspective
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Publication:829489
DOI10.1007/s11228-020-00552-2zbMath1467.90028OpenAlexW3083323082MaRDI QIDQ829489
Publication date: 6 May 2021
Published in: Set-Valued and Variational Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11228-020-00552-2
Related Items (6)
Gradient formulae for probability functions depending on a heterogenous family of constraints ⋮ On the algorithmic solution of optimization problems subject to probabilistic/robust (probust) constraints ⋮ Probability maximization via Minkowski functionals: convex representations and tractable resolution ⋮ Probability functions generated by set-valued mappings: a study of first order information ⋮ A derivative-free trust-region algorithm with copula-based models for probability maximization problems ⋮ Generalized differentiation of probability functions: parameter dependent sets given by intersections of convex sets and complements of convex sets
Uses Software
Cites Work
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- Decomposition algorithms for two-stage chance-constrained programs
- Nonlinear chance constrained problems: optimality conditions, regularization and solvers
- On the quantification of nomination feasibility in stationary gas networks with random load
- A branch-and-cut decomposition algorithm for solving chance-constrained mathematical programs with finite support
- Level bundle methods for constrained convex optimization with various oracles
- Convex proximal bundle methods in depth: a unified analysis for inexact oracles
- A characterization of the subdifferential of singular Gaussian distribution functions
- Convexity of Gaussian chance constraints and of related probability maximization problems
- An integer programming approach for linear programs with probabilistic constraints
- Implementable algorithm for stochastic optimization using sample average approximations
- Convexity of chance constraints with independent random variables
- Stability analysis for stochastic programs
- 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
- Metric regularity and quantitative stability in stochastic programs with probabilistic constraints.
- Global probability maximization for a Gaussian bilateral inequality in polynomial time
- Properties of chance constraints in infinite dimensions with an application to PDE constrained optimization
- (Sub-)differentiability of probability functions with elliptical distributions
- Subdifferential characterization of probability functions under Gaussian distribution
- The Benders decomposition algorithm: a literature review
- Stochastic linear programming. Models, theory, and computation
- Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations
- Hölder and Lipschitz stability of solution sets in programs with probabilistic constraints
- Derivatives of probability functions and integrals over sets given by inequalities
- Derivatives of probability functions and some applications
- Differentiation of probability functions: The transformation method
- Distributionally robust joint chance constraints with second-order moment information
- Lipschitz and differentiability properties of quasi-concave and singular normal distribution functions
- Gradient formulae for nonlinear probabilistic constraints with non-convex quadratic forms
- Convex set functions in \(d\)-space
- Proximal bundle methods for nonsmooth DC programming
- Nonsmooth and nonconvex optimization via approximate difference-of-convex decompositions
- A distributionally robust perspective on uncertainty quantification and chance constrained programming
- Probabilistic constraints via SQP solver: application to a renewable energy management problem
- Joint chance constrained programming for hydro reservoir management
- Second-order differentiability of probability functions
- Inexact stabilized Benders' decomposition approaches with application to chance-constrained problems with finite support
- Eventual convexity of probability constraints with elliptical distributions
- On mixing sets arising in chance-constrained programming
- Extensions of stochastic optimization results to problems with system failure probability functions
- Convexity and optimization with copulæ structured probabilistic constraints
- A Gradient Formula for Linear Chance Constraints Under Gaussian Distribution
- Distributionally Robust Convex Optimization
- On Shape Optimization with Stochastic Loadings
- Sequential Convex Approximations to Joint Chance Constrained Programs: A Monte Carlo Approach
- Constrained Bundle Methods for Upper Inexact Oracles with Application to Joint Chance Constrained Energy Problems
- GloptiPoly 3: moments, optimization and semidefinite programming
- An Integer Programming and Decomposition Approach to General Chance-Constrained Mathematical Programs
- A Sample Approximation Approach for Optimization with Probabilistic Constraints
- Lectures on Stochastic Programming
- Approximate Volume and Integration for Basic Semialgebraic Sets
- A Barrier Method for Large-Scale Constrained Optimization
- Differentiability of probability function
- Approximations for Probability Distributions and Stochastic Optimization Problems
- Probabilistic Partial Set Covering with an Oracle for Chance Constraints
- A differentiation formula for integrals overseas given by inclusion
- 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
- An Inner-Outer Approximation Approach to Chance Constrained Optimization
- The Supporting Hyperplane Method for Unimodal Programming
- On the Convergence of Some Feasible Direction Algorithms for Nonlinear Programming
- A class of stochastic programming decision problems
- Tail Conditional Expectations for Elliptical Distributions
- Convergence Analysis for Mathematical Programs with Distributionally Robust Chance Constraint
- Bundle Method for Non-Convex Minimization with Inexact Subgradients and Function Values
- Numerical optimization. Theoretical and practical aspects. Transl. from the French
- A proximal bundle method for nonsmooth nonconvex functions with inexact information
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