Gradient-based simulation optimization under probability constraints

DOI10.1016/j.ejor.2011.01.049zbMath1242.90141OpenAlexW2093443222MaRDI QIDQ421531

Laetitia Andrieu, Felisa J. Vázquez-Abad, Guy Cohen

Publication date: 14 May 2012

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2011.01.049

zbMATH Keywords

stochastic approximationstochastic gradient algorithmprobability constraints

Mathematics Subject Classification ID

Stochastic programming (90C15) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (6)

A direct search method for unconstrained quantile-based simulation optimization ⋮ Stochastic Nelder-Mead simplex method -- a new globally convergent direct search method for simulation optimization ⋮ A sampling criterion for constrained Bayesian optimization with uncertainties ⋮ Two approaches to stochastic optimal control problems with a final-time expectation constraint ⋮ A New Unbiased Stochastic Derivative Estimator for Discontinuous Sample Performances with Structural Parameters ⋮ Indirect inference with a non-smooth criterion function

Cites Work

• Measure-valued differentiation for Markov chains
• Introduction to Stochastic Programming
• Budget-Dependent Convergence Rate of Stochastic Approximation
• Sensitivity analysis for ruin probabilities: canonical risk model
• The Minimization of Semicontinuous Functions: Mollifier Subgradients
• Ill-conditioned performance functions of queueing systems
• Probability Gradient Estimation by Set-Valued Calculus and Applications in Network Design
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