| Description |
1 online resource (xii, 101 pages) |
| Series |
Lecture notes in computer science ; 769 |
|
Lecture notes in computer science ; 769.
|
| Contents |
Motivation -- The metric-based Cauchy perspective -- The model-based Newton perspective -- The Newton-Cauchy framework -- Convergent implementable algorithms -- Unconstrained optimization technology |
| Summary |
Computational unconstrained nonlinear optimization comes to life from a study of the interplay between the metric-based (Cauchy) and model-based (Newton) points of view. The motivating problem is that of minimizing a convex quadratic function. This research monograph reveals for the first time the essential unity of the subject. It explores the relationships between the main methods, develops the Newton-Cauchy framework and points out its rich wealth of algorithmic implications and basic conceptual methods. The monograph also makes a valueable contribution to unifying the notation and terminology of the subject. It is addressed topractitioners, researchers, instructors, and students and provides a useful and refreshing new perspective on computational nonlinear optimization |
| Bibliography |
Includes bibliographical references (pages 91-101) |
| Subject |
Nonlinear programming.
|
|
Mathematical optimization.
|
|
Mathematical optimization
|
|
Nonlinear programming
|
|
Niet-lineaire programmering.
|
|
Optimaliseren.
|
| Genre/Form |
Congressen (vorm)
|
| Form |
Electronic book
|
| ISBN |
9783540483106 |
|
3540483101 |
|
