Mixed Integer Nonlinear Programming
Sven Leyffer
Guardado en:
| Autor principal: | |
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| Otros Autores: | |
| Formato: | Conference Paper |
| Lenguaje: | inglés |
| Publicado: |
New York, NY
Springer Science+Business Media, LLC
2012
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| Colección: | The IMA Volumes in Mathematics and its Applications
154 |
| In: |
The IMA volumes in mathematics and its applications (154)
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| Volumes / Articles: | Show Volumes / Articles. |
| DOI: | 10.1007/978-1-4614-1927-3 |
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| Acceso en línea: | 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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| Notas de Autor: | edited by Jon Lee, Sven Leyffer |
| Sumario: | 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 |
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| Notas: | Description based upon print version of record |
| Descripción Física: | Online Resource |
| ISBN: | 9781461419273 9781283446433 |
| DOI: | 10.1007/978-1-4614-1927-3 |