Nonconvex Generalized Benders Decomposition for Stochastic Separable Mixed-Integer Nonlinear Programs

Nonconvex Generalized Benders Decomposition for Stochastic Separable Mixed-Integer Nonlinear Programs

This paper considers deterministic global optimization of scenario-based, two-stage stochastic mixed-integer nonlinear programs (MINLPs) in which the participating functions are nonconvex and separable in integer and continuous variables. A novel decomposition method based on generalized Benders dec...

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Bibliographic Details
Main Authors: Li, Xiang, Tomasgard, Asgeir, Barton, Paul I
Other Authors: Massachusetts Institute of Technology. Process Systems Engineering Laboratory
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2019
Online Access:https://hdl.handle.net/1721.1/122814

Internet

https://hdl.handle.net/1721.1/122814

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