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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.
| ISBN: | 9780792346807 |
| Publication date: | 31st August 1997 |
| Author: | T Rapcsák |
| Publisher: | Springer an imprint of Springer US |
| Format: | Hardback |
| Pagination: | 374 pages |
| Series: | Nonconvex Optimization and Its Applications |
| Genres: |
Optimization Stochastics Differential and Riemannian geometry Management decision making Operational research Discrete mathematics Geometry Probability and statistics Software Engineering |
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.
Smooth Nonlinear Optimization in R[superscript N] features in the following genres: Optimization, Stochastics, Differential and Riemannian geometry, Management decision making, Operational research, Discrete mathematics, Geometry, Probability and statistics, Software Engineering
Smooth Nonlinear Optimization in R[superscript N] is available in Hardback
Smooth Nonlinear Optimization in R[superscript N] was written by T Rapcsák and published by Springer an imprint of Springer US
Smooth Nonlinear Optimization in R[superscript N] has 374 pages
Yes it is part of Nonconvex Optimization and Its Applications series