Numerical probabilistic approach for optimization problems

Описание

Тип публикации: статья из журнала (материалы конференций, опубликованные в журналах)

Конференция: GAMM-IMACS International Symposium on Scientific Computing, Computer Arithmetic, and Validated Numerics (SCAN); Wurzburg, Germany ; Wurzburg, Germany

Год издания: 2016

Идентификатор DOI: 10.1007/978-3-319-31769-4_4

Ключевые слова: Optimization, Joint probability density function, New approaches, Numerical probability analysis, Optimization problems, Probabilistic approaches, Random input, Random programming, Probability density function

Аннотация: In the paper a new approach to optimization problems with random input parameters, which is defined as random programming, is discussed. This approach uses a numerical probability analysis and allows us to construct the set of solutions of an optimization problem based on the joint probability density function. © Springer InternatiПоказать полностьюonal Publishing Switzerland 2016.

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Издание

Журнал: (21 September 2014 through 26 September 2014

Выпуск журнала: Vol. 9553

Номера страниц: 43-53

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