Chance-constrained problems and rare events: an importance sampling approach
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Publication:291054
DOI10.1007/s10107-015-0942-xzbMath1356.90093OpenAlexW1459610841WikidataQ57707454 ScholiaQ57707454MaRDI QIDQ291054
Bernardo K. Pagnoncelli, Tito Homem-de-mello, Javiera Barrera, Gianpiero Canessa, Eduardo Moreno
Publication date: 6 June 2016
Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10107-015-0942-x
Monte Carlo methods (65C05) Stochastic programming (90C15) Network design and communication in computer systems (68M10)
Related Items (14)
Solving joint chance constrained problems using regularization and Benders' decomposition ⋮ On the mixing set with a knapsack constraint ⋮ Importance Sampling in Stochastic Programming: A Markov Chain Monte Carlo Approach ⋮ Optimization under Rare Chance Constraints ⋮ Approximation of probabilistic constraints in stochastic programming problems with a probability measure kernel ⋮ Chance-constrained optimization under limited distributional information: a review of reformulations based on sampling and distributional robustness ⋮ Joint chance-constrained multi-objective multi-commodity minimum cost network flow problem with copula theory ⋮ A Sequential Algorithm for Solving Nonlinear Optimization Problems with Chance Constraints ⋮ On the Convexity of Level-sets of Probability Functions ⋮ Minimization of a class of rare event probabilities and buffered probabilities of exceedance ⋮ Variance reduction for sequential sampling in stochastic programming ⋮ Stochastic mathematical programs with probabilistic complementarity constraints: SAA and distributionally robust approaches ⋮ Generalized Differentiation of Probability Functions Acting on an Infinite System of Constraints ⋮ Problem-driven scenario generation: an analytical approach for stochastic programs with tail risk measure
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