parametric optimization singularities pathfollowing de guddat (9 résultats)

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hardcover. Etat : Very Good. John Wiley & Sons; New York, 1990. Hardcover. A Very Good, binding sturdy and intact, some handling/scuffing to boards, mild crimping to spine edges, small dent bottom rear board edge, bit of age toning to pages, offsetting to half title and verso and also page 191 and verso, some offsetting to front board, without Dust wrapper. A nice, clean and unmarked copy. 8vo[octavo or approx. 6 x 9 inches]. 191pp., indexed. We pack securely and ship daily with delivery confirmation on every book. Please Note: Depending on site, actual book for sale may differ physically from picture listed. Additional scan(s) are available for any item, please inquire.Please note: Oversized books/sets MAY require additional postage then what is quoted for 2.2lb book.

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Paperback. Etat : Brand New. 199 pages. German language. 9.60x6.69x0.55 inches. In Stock.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume is intended for readers who, whether they be mathematicians, workers in other fields or students, are familiar with the basic approaches and methods of mathematical optimization. The subject matter is concerned with optimization problems in which some or all of the individual data involved depend on one parameter. Such problems are called one-parametric optimization problems. Solution algorithms for such problems are of interest for several reasons. We consider here mainly applications of solution algorithms for one-parametric optimization problems in the following fields: (i) globally convergent algorithms for nonlinear, in particular non-convex, optimization problems, (ii) global optimization, (iii) multi-objective optimization. The main tool for a solution algorithm for a one-parametric optimization problem will be the so-called pathfollowing methods (also called continuation or homotopy methods) (cf. Chapters 3 and 4). Classical methods in the set of stationary points will be extended to the set of all generalized critical points. This could be helpful since the path of stationary points stops in this set, but there is a continuation in the broader set of generalized critical points. However, it will be shown that pathfollowing methods only are not successful in every case. This is the reason why we propose to jump from one connected component in the set of local minimizers and generalized critical points, respectively, to another one (Chapter 5).

Taschenbuch. Etat : Neu. Parametric Optimization: Singularities, Pathfollowing and Jumps | J. Guddat (u. a.) | Taschenbuch | viii | Deutsch | 1990 | Vieweg & Teubner | EAN 9783519021124 | Verantwortliche Person für die EU: Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume is intended for readers who, whether they be mathematicians, workers in other fields or students, are familiar with the basic approaches and methods of mathematical optimization. The subject matter is concerned with optimization problems in which some or all of the individual data involved depend on one parameter. Such problems are called one-parametric optimization problems. Solution algorithms for such problems are of interest for several reasons. We consider here mainly applications of solution algorithms for one-parametric optimization problems in the following fields: (i) globally convergent algorithms for nonlinear, in particular non-convex, optimization problems, (ii) global optimization, (iii) multi-objective optimization. The main tool for a solution algorithm for a one-parametric optimization problem will be the so-called pathfollowing methods (also called continuation or homotopy methods) (cf. Chapters 3 and 4). Classical methods in the set of stationary points will be extended to the set of all generalized critical points. This could be helpful since the path of stationary points stops in this set, but there is a continuation in the broader set of generalized critical points. However, it will be shown that pathfollowing methods only are not successful in every case. This is the reason why we propose to jump from one connected component in the set of local minimizers and generalized critical points, respectively, to another one (Chapter 5). 200 pp. Deutsch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 1 Introduction.- 2 Theoretical Background.- 3 Pathfollowing of Curves of Local Minimizers.- 4 Pathfollowing Along a Connected Component in the Karush-Kuhn-Tucker Set and in the Critical Set.- 5 Pathfollowing with Jumps in the Set of Local Minimizers and in .

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This volume is intended for readers who, whether they be mathematicians, workers in other fields or students, are familiar with the basic approaches and methods of mathematical optimization. The subject matter is concerned with optimization problems in which some or all of the individual data involved depend on one parameter. Such problems are called one-parametric optimization problems. Solution algorithms for such problems are of interest for several reasons. We consider here mainly applications of solution algorithms for one-parametric optimization problems in the following fields: (i) globally convergent algorithms for nonlinear, in particular non-convex, optimization problems, (ii) global optimization, (iii) multi-objective optimization. The main tool for a solution algorithm for a one-parametric optimization problem will be the so-called pathfollowing methods (also called continuation or homotopy methods) (cf. Chapters 3 and 4). Classical methods in the set of stationary points will be extended to the set of all generalized critical points. This could be helpful since the path of stationary points stops in this set, but there is a continuation in the broader set of generalized critical points. However, it will be shown that pathfollowing methods only are not successful in every case. This is the reason why we propose to jump from one connected component in the set of local minimizers and generalized critical points, respectively, to another one (Chapter 5).Vieweg+Teubner Verlag, Abraham-Lincoln-Straße 46, 65189 Wiesbaden 200 pp. Deutsch.