Stochastic approximation methods in stochastic optimization
Data(s) |
19/11/2013
19/11/2013
2013
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Resumo |
Stochastic approximation methods for stochastic optimization are considered. Reviewed the main methods of stochastic approximation: stochastic quasi-gradient algorithm, Kiefer-Wolfowitz algorithm and adaptive rules for them, simultaneous perturbation stochastic approximation (SPSA) algorithm. Suggested the model and the solution of the retailer's profit optimization problem and considered an application of the SQG-algorithm for the optimization problems with objective functions given in the form of ordinary differential equation. |
Identificador |
http://www.doria.fi/handle/10024/93687 URN:NBN:fi-fe201311197362 |
Idioma(s) |
en |
Palavras-Chave | #stochastic optimization #deterministic equivalent #stochastic quasi-gradient algorithm (SQG) #conditional value-at-risk (CVaR) #mean-value #value-at-risk (VaR) |
Tipo |
Master's thesis Diplomityö |