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Random time-shift approximation enables hierarchical Bayesian inference of mechanistic within-host viral dynamics models on large datasets. [PDF]
PLoS Comput BiolMorris DJ, Kennedy L, Black AJ.
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Distributionally Robust Two-Stage Stochastic Programming
SIAM Journal on Optimization, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Daniel Duque +2 more
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Two‐stage stochastic integer programming: a survey
Statistica Neerlandica, 1996Stochastic integer programming is more complicated than stochastic linear programming, as will be explained for the case of the two‐stage stochastic programming model. A survey of the results accomplished in this recent field of research is given.
Schultz, R. +2 more
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Two-Stage Stochastic Variational Inequality Arising from Stochastic Programming
Journal of Optimization Theory and Applications, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Min Li, Chao Zhang
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Stability in Two-Stage Stochastic Programming
SIAM Journal on Control and Optimization, 1987We analyze the effect of changes in problem functions and/or distributions in certain two-stage stochastic programming problems with recourse. Under reasonable assumptions the locally optimal value of the perturbed problem will be continuous and the corresponding set of local optimizers will be upper semicontinuous with respect to the parameters ...
Robinson, Stephen M., Wets, Roger J.-B.
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Convergence Properties of Two-Stage Stochastic Programming
Journal of Optimization Theory and Applications, 2000The aim of the authors is to investigate a convergence rate of empirical estimates in the case of stochastic programming problems with mathematical expectation in the objective function and a ``deterministic'' constraint set. Of course, two-stage stochastic programming problems belong to this type of the problems. First, they recall a (rather complete)
Dai, L., Chen, C. H., Birge, J. R.
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Two-Stage Stochastic Programs with Mixed Probabilities
SIAM Journal on Optimization, 2007Summary: We extend the traditional two-stage linear stochastic program by probabilistic constraints imposed in the second stage. This adds nonlinearity such that basic arguments for analyzing the structure of linear two-stage stochastic programs have to be rethought from the very beginning.
Bosch, Paul +2 more
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Asymptotic Results of Stochastic Decomposition for Two-Stage Stochastic Quadratic Programming
SIAM Journal on Optimization, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Junyi Liu, Suvrajeet Sen
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Sequential Bounding Methods for Two-Stage Stochastic Programs
INFORMS Journal on Computing, 2016In rare situations, stochastic programs can be solved analytically. Otherwise, approximation is necessary to solve stochastic programs with a large or infinite number of scenarios to a desired level of accuracy. This involves statistical sampling or deterministic selection of a finite set of scenarios to obtain a tractable deterministic equivalent ...
Gose, Alexander H., Denton, Brian T.
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Limited recourse in two-stage stochastic linear programs
Journal of Information and Optimization Sciences, 2003In several real-world applications, modelled by two-stage stochastic problems, first and second-stage decisions (or some of their components) represent identical variables of the problem that is modelled. In these cases an appropriate solution of the problem might require that the second-stage decisions do not differ substantially from the ...
P. BERALDI +3 more
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