Mixed Integer Nonlinear Programming

Sven Leyffer

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Bibliographic Details
Main Author: Lee, Jon (Author)
Other Authors: Leyffer, Sven (Other)
Format: Conference Paper
Language:English
Published: New York, NY Springer Science+Business Media, LLC 2012
Series:The IMA Volumes in Mathematics and its Applications 154
In: The IMA volumes in mathematics and its applications (154)

Volumes / Articles: Show Volumes / Articles.
DOI:10.1007/978-1-4614-1927-3
Subjects:
Online Access:Resolving-System, lizenzpflichtig, Volltext: http://dx.doi.org/10.1007/978-1-4614-1927-3
Verlag, Zentralblatt MATH, Inhaltstext: https://zbmath.org/?q=an:1230.90005
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Author Notes:edited by Jon Lee, Sven Leyffer
Description
Summary:Sven Leyffer
Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the mos
Item Description:Description based upon print version of record
Physical Description:Online Resource
ISBN:9781461419273
9781283446433
DOI:10.1007/978-1-4614-1927-3