Stochastic approximation methods in stochastic optimization


Autoria(s): Bobylev, Ilya
Data(s)

19/11/2013

19/11/2013

2013

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