Smooth Nonlinear Optimization in R n:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
1997
|
| Schriftenreihe: | Nonconvex Optimization and Its Applications
19 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Experience gained during a ten-year long involvement in modelling, program ming and application in nonlinear optimization helped me to arrive at the conclusion that in the interest of having successful applications and efficient software production, knowing the structure of the problem to be solved is in dispensable. This is the reason why I have chosen the field in question as the sphere of my research. Since in applications, mainly from among the nonconvex optimization models, the differentiable ones proved to be the most efficient in modelling, especially in solving them with computers, I started to deal with the structure of smooth optimization problems. The book, which is a result of more than a decade of research, can be equally useful for researchers and stu dents showing interest in the domain, since the elementary notions necessary for understanding the book constitute a part of the university curriculum. I in tended dealing with the key questions of optimization theory, which endeavour, obviously, cannot bear all the marks of completeness. What I consider the most crucial point is the uniform, differential geometric treatment of various questions, which provides the reader with opportunities for learning the structure in the wide range, within optimization problems. I am grateful to my family for affording me tranquil, productive circumstances. I express my gratitude to F. |
| Beschreibung: | 1 Online-Ressource (XIV, 376 p) |
| ISBN: | 9781461563570 9781461379201 |
| ISSN: | 1571-568X |
| DOI: | 10.1007/978-1-4615-6357-0 |
Internformat
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Datensatz im Suchindex
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| author | Rapcsák, Tamás |
| author_facet | Rapcsák, Tamás |
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| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
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| dewey-search | 519.6 |
| dewey-sort | 3519.6 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4615-6357-0 |
| format | Electronic eBook |
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| isbn | 9781461563570 9781461379201 |
| issn | 1571-568X |
| language | English |
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| spelling | Rapcsák, Tamás Verfasser aut Smooth Nonlinear Optimization in R n by Tamás Rapcsák Boston, MA Springer US 1997 1 Online-Ressource (XIV, 376 p) txt rdacontent c rdamedia cr rdacarrier Nonconvex Optimization and Its Applications 19 1571-568X Experience gained during a ten-year long involvement in modelling, program ming and application in nonlinear optimization helped me to arrive at the conclusion that in the interest of having successful applications and efficient software production, knowing the structure of the problem to be solved is in dispensable. This is the reason why I have chosen the field in question as the sphere of my research. Since in applications, mainly from among the nonconvex optimization models, the differentiable ones proved to be the most efficient in modelling, especially in solving them with computers, I started to deal with the structure of smooth optimization problems. The book, which is a result of more than a decade of research, can be equally useful for researchers and stu dents showing interest in the domain, since the elementary notions necessary for understanding the book constitute a part of the university curriculum. I in tended dealing with the key questions of optimization theory, which endeavour, obviously, cannot bear all the marks of completeness. What I consider the most crucial point is the uniform, differential geometric treatment of various questions, which provides the reader with opportunities for learning the structure in the wide range, within optimization problems. I am grateful to my family for affording me tranquil, productive circumstances. I express my gratitude to F. Mathematics Discrete groups Global differential geometry Mathematical optimization Operations research Optimization Operation Research/Decision Theory Differential Geometry Convex and Discrete Geometry Mathematik Nichtlineare Optimierung (DE-588)4128192-5 gnd rswk-swf Lineare Optimierung (DE-588)4035816-1 gnd rswk-swf Lineare Optimierung (DE-588)4035816-1 s 1\p DE-604 Nichtlineare Optimierung (DE-588)4128192-5 s 2\p DE-604 https://doi.org/10.1007/978-1-4615-6357-0 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Rapcsák, Tamás Smooth Nonlinear Optimization in R n Mathematics Discrete groups Global differential geometry Mathematical optimization Operations research Optimization Operation Research/Decision Theory Differential Geometry Convex and Discrete Geometry Mathematik Nichtlineare Optimierung (DE-588)4128192-5 gnd Lineare Optimierung (DE-588)4035816-1 gnd |
| subject_GND | (DE-588)4128192-5 (DE-588)4035816-1 |
| title | Smooth Nonlinear Optimization in R n |
| title_auth | Smooth Nonlinear Optimization in R n |
| title_exact_search | Smooth Nonlinear Optimization in R n |
| title_full | Smooth Nonlinear Optimization in R n by Tamás Rapcsák |
| title_fullStr | Smooth Nonlinear Optimization in R n by Tamás Rapcsák |
| title_full_unstemmed | Smooth Nonlinear Optimization in R n by Tamás Rapcsák |
| title_short | Smooth Nonlinear Optimization in R n |
| title_sort | smooth nonlinear optimization in r n |
| topic | Mathematics Discrete groups Global differential geometry Mathematical optimization Operations research Optimization Operation Research/Decision Theory Differential Geometry Convex and Discrete Geometry Mathematik Nichtlineare Optimierung (DE-588)4128192-5 gnd Lineare Optimierung (DE-588)4035816-1 gnd |
| topic_facet | Mathematics Discrete groups Global differential geometry Mathematical optimization Operations research Optimization Operation Research/Decision Theory Differential Geometry Convex and Discrete Geometry Mathematik Nichtlineare Optimierung Lineare Optimierung |
| url | https://doi.org/10.1007/978-1-4615-6357-0 |
| work_keys_str_mv | AT rapcsaktamas smoothnonlinearoptimizationinrn |