The Sample Average Approximation Method for Stochastic Discrete Optimization [PDF]
SIAM Journal on Optimization, 2002 The authors study a Monte Carlo simulation-based approach to stochastic discrete optimization problems of the form \(\min_{x\in S}\{g(x):= E_PG(x, W)\}\), where \(W\) is a random vector having probability distribution \(P\), \(S\) is a finite set, \(G(x,w)\) is a real-valued function of two (vector) variables \(x\) and \(w\), and \(E_PG(x, W)= \int G(x,
Kleywegt, Anton J. +2 more
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A galaxy-halo model of large-scale structure [PDF]
, 2005 We present a new, galaxy-halo model of large-scale structure, in which the galaxies entering a given sample are the fundamental objects. Haloes attach to galaxies, in contrast to the standard halo model, in which galaxies attach to haloes.
Andrew J. S. Hamilton +31 more
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Partial sample average approximation method for chance constrained problems [PDF]
Optimization Letters, 2018 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cheng, Jianqiang +2 more
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Symmetric confidence regions and confidence intervals for normal map formulations of stochastic variational inequalities [PDF]
, 2014 Stochastic variational inequalities (SVI) model a large class of equilibrium problems subject to data uncertainty, and are closely related to stochastic optimization problems.
Lu, Shu
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Design of micromachines under uncertainty with the sample-average approximation method
Journal of Advanced Mechanical Design, Systems, and ManufacturingVariability in the features produced by microfabrication processes, as well as uncertainty in some material properties, may cause a significant deviation in the performance of micromachines within the same fabrication run.
Jorge Mario MONSALVE GUARACAO +5 more
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Coupling Importance Sampling and Multilevel Monte Carlo using Sample Average Approximation [PDF]
Methodology and Computing in Applied Probability, 2017 In this work, we propose a smart idea to couple importance sampling and Multilevel Monte Carlo (MLMC). We advocate a per level approach with as many importance sampling parameters as the number of levels, which enables us to compute the different levels independently.
Ahmed Kebaier, Jérôme Lelong
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Landauer-B\"uttiker and Thouless conductance [PDF]
, 2014 In the independent electron approximation, the average (energy/charge/entropy) current flowing through a finite sample S connected to two electronic reservoirs can be computed by scattering theoretic arguments which lead to the famous Landauer-B\"uttiker
Bruneau, Laurent +3 more
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A Bilateral Tradeoff Decision Model for Wind Power Utilization with Extensive Load Scheduling
Applied Sciences, 2019 In this paper, we present the extensive load scheduling problem with intermittent and uncertain wind power availability. A chance-constrained bilateral tradeoff decision model is established to solve the problem.
Qingshan Xu +3 more
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IEEE Access, 2020 This study addresses the problem of optimally locating vehicle inspection facilities under uncertain customer demand and varying velocity considering regional constraints.
Peng Wu +4 more
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Nonparametric Approximation Strategy Iteration Parallel Reinforcement Learning Algorithm [PDF]
Jisuanji gongcheng, 2018 To solve the problem of slow convergence speed of the online approximation strategy iteration reinforcement learning algorithm,a nonparametric approximation strategy iteration parallel reinforcement learning algorithm is proposed.The number of parallel ...
JI Ting,ZHANG Hua
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