Joint chance-constrained reliability optimization with general form of distributions

Descripción del Articulo

Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty. Stochastic programming models arise as reformulations or extensions of reliability optimization problems with random parameters. Moreover, the resource elements vary and it is reasonab...

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Detalles Bibliográficos
Autores: Vincent, Charles, Islam Ansari, Saifu, Khodabakhshi, Mohammad
Formato: documento de trabajo
Fecha de Publicación:2014
Institución:Pontificia Universidad Católica del Perú
Repositorio:PUCP-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.pucp.edu.pe:20.500.14657/166794
Enlace del recurso:https://repositorio.pucp.edu.pe/index/handle/123456789/166794
http://dx.doi.org/10.7835/ccwp-2014-01-0005
Nivel de acceso:acceso abierto
Materia:Chance-constrained programming
Reliability optimization
Joint constraints
General form of distributions
http://purl.org/pe-repo/ocde/ford#5.02.04
Descripción
Sumario:Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty. Stochastic programming models arise as reformulations or extensions of reliability optimization problems with random parameters. Moreover, the resource elements vary and it is reasonable to consider them as stochastic variables. In this paper, we describe the chance-constrained reliability stochastic optimization (CCRSO) problem for which the objective is to maximize the system reliability for the given joint chance constraints where only the resource variables are random in nature and which follow different general form of distributions. Few numerical examples are also presented to illustrate the applicability of the methodology.
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