Joint dynamic probabilistic constraints with projected linear decision rules

Resumo

We consider multistage stochastic linear optimization problems combining joint dynamic probabilistic constraints with hard constraints. We develop a method for projecting decision rules onto hard constraints of wait-and-see type. We establish the relation between the original (in nite dimensional) problem and approximating problems working with projections from di erent subclasses of decision policies. Considering the subclass of linear decision rules and a generalized linear model for the underlying stochastic process with noises that are Gaussian or truncated Gaussian, we show that the value and gradient of the objective and constraint functions of the approximating problems can be computed analytically.

Ficha do documento

Tipo

Artigo científico

Ano

2016

Instituição

EMAp - Escola de Matemática Aplicada

Fonte

Repositório da FGV

Idioma

Inglês

Acesso

Não informado

Identificador

oai:repositorio.fgv.br:10438/16240

Temas

EconomiaDados

Palavras-chave

Multistage stochastic linear programsLinear decision rulesDynamic probabilistic constraintsEconomiaProcesso estocásticoProbabilidadesDecisão estatística