Results 251 to 260 of about 947,067 (264)

Sample average approximation methods for stochastic MINLPs

Computers & Chemical Engineering, 2004
One approach to process design with uncertain parameters is to formulate a stochastic MINLP. When there are many uncertain parameters, the number of samples becomes unmanageably large and computing the solution to the MINLP can be difficult and very time consuming.
Jing Wei, Matthew J. Realff
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Acceleration on Adaptive Importance Sampling with Sample Average Approximation

SIAM Journal on Scientific Computing, 2017
Summary: We construct and analyze acceleration techniques for adaptive Monte Carlo simulations for general multivariate probability laws when the sample average approximation is employed for optimal parameter search. Our goal is to accelerate the adaptive Monte Carlo estimation by leading the parameter search line based on the sample average ...
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Enhancing the sample average approximation method with U designs

Biometrika, 2010
Summary: Many computational problems in statistics can be cast as stochastic programs that are optimization problems whose objective functions are multi-dimensional integrals. The sample average approximation method is widely used for solving such a problem, which first constructs a sampling-based approximation to the objective function and then finds ...
Qi Tang, Peter Z. G. Qian
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A Guide to Sample Average Approximation

2014
This chapter reviews the principles of sample average approximation (SAA) for solving simulation optimization problems. We provide an accessible overview of the area and survey interesting recent developments. We explain when one might want to use SAA and when one might expect it to provide good-quality solutions.
Sujin Kim, Raghu Pasupathy, Shane G. Henderson   +2 more
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Sample Average Approximation For Functional Decisions Under Shape Constraints

2020 Winter Simulation Conference (WSC), 2020
Sample average approximation methods are most often applied when the set of decision variables is finite. This research develops a method of finding optimal solutions to infinite-dimensional simulation optimization problems when the decision variable is a monotone function on a random variable used to model the uncertainty itself.
Dashi I. Singham, Henry Lam
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Sample average approximation of expected value constrained stochastic programs

Operations Research Letters, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wang, Wei, Ahmed, Shabbir
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Sample Average Approximation Method for Compound Stochastic Optimization Problems

SIAM Journal on Optimization, 2013
The paper studies stochastic optimization (programming) problems with compound functions containing expectations and extreme values of other random functions as arguments. Compound functions arise in various applications. A typical example is a variance function of nonlinear outcomes.
Ermoliev, Y.M., Norkin, V.
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Stochastic Variational Inequalities: Residual Minimization Smoothing Sample Average Approximations

SIAM Journal on Optimization, 2012
The stochastic variational inequality (VI) has been used widely in engineering and economics as an effective mathematical model for a number of equilibrium problems involving uncertain data. This paper presents a new expected residual minimization (ERM) formulation for a class of stochastic VI.
Chen, X, Wets, RJ, Zhang, Y
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Sample Average Approximation Technique for Flexible Network Design Problem

Journal of Computing in Civil Engineering, 2011
Finding an optimal investment strategy to use scarce resources efficiently is challenging, since the transportation network parameters such as demand, capacity, and travel cost are uncertain. Sequencing investments over time can give flexibility to the planner so as to change, delay, or even abandon the future investment based on system realization ...
PATIL, GR, UKKUSURI, SV
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Quantifying uncertainty in sample average approximation

2015 Winter Simulation Conference (WSC), 2015
Henry Lam, null Enlu Zhou
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