A decomposition-based solution method for stochastic mixed integer nonlinear programs

This is a summary of the main results presented in the author’s PhD thesis, supervised by D. Conforti and P. Beraldi and defended on March 2005. The thesis, written in English, is available from the author upon request. It describes one of the very few existing implementations of a method for solvin...

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Bibliographic Details
Published in:4OR Vol. 4; no. 4; pp. 343 - 346
Main Author: Bruni, Maria Elena
Format: Journal Article
Language:English
Published: Heidelberg Springer Nature B.V 01.12.2006
Subjects:
Algorithms
Global optimization
Mixed integer
Nonlinear programming
Operations research
Stochastic programming
Studies
ISSN:1619-4500, 1614-2411
Online Access:Get full text
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Summary:This is a summary of the main results presented in the author’s PhD thesis, supervised by D. Conforti and P. Beraldi and defended on March 2005. The thesis, written in English, is available from the author upon request. It describes one of the very few existing implementations of a method for solving stochastic mixed integer nonlinear programming problems based on deterministic global optimization. In order to face the computational challenge involved in the solution of such multi-scenario nonconvex problems, a branch and bound approach is proposed that exploits the peculiar structure of stochastic programming problem.
Bibliography:ObjectType-Article-1
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ISSN:1619-4500
1614-2411
DOI:10.1007/s10288-006-0007-3