The Sample Average Approximation Method for Stochastic Discrete Optimization
نویسندگان
چکیده
منابع مشابه
The Sample Average Approximation Method for Stochastic Discrete Optimization
In this paper we study a Monte Carlo simulation–based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and the expected value function is approximated by the corresponding sample average function. The obtained sample average optimization problem is solved, and the procedure is repeated several times until a stopping crite...
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We consider the Sample Average Approximation (SAA) method for 2-stage stochastic optimization problems with recourse and prove a polynomial time convergence theorem for the SAA method. In the 2-stage recourse model, where one makes decisions in two steps. First, given only distributional information about (some of) the data, one commits on initial (first-stage) actions, and then once the actual...
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Sample Average Approximation (SAA) is a well-known method for solving stochastic programs. Here, we attempt to scale up the SAA method to harder problems than those previously studied. We argue that to apply the SAA method effectively, there are three parameters to optimize: the number of evaluations, the number of scenarios, and the number of candidate solutions. We propose an experimental met...
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ژورنال
عنوان ژورنال: SIAM Journal on Optimization
سال: 2002
ISSN: 1052-6234,1095-7189
DOI: 10.1137/s1052623499363220