Temat: Lagrange - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Raport Badawczy = Research Report ; RB/57/2006
Lagrangian Relaxation via Ballstep Subgradient Methods
Autorzy:: Kiwiel, Krzysztof
Lindberg, Per
Larsson, Torbjörn
Wydawca:: Instytut Badań Systemowych. Polska Akademia Nauk
Systems Research Institute. Polish Academy of Sciences
Powiązania:: Raport Badawczy = Research Report
Opis:: 19 stron ; 21 cm
19 pages ; 21 cm
Bibliography p. 18-19
Bibliografia s. 18-19
The paper demonstrates useful properties of ballstep subgradient methods for convex optimization that use level controls for estimating the optimal value. Augmented with simple averaging schemes, they asymptotically find objective and constraint subgradients involved in optimality conditions. When applied to Lagrangian relaxation of convex programs, they find both primal and dual solutions, and have practicable stopping criteria. Up till now, similar results have only been known for proximal bundle methods, and for subgradient methods with divergent series stepsizes, whose convergence can be slow. Encouraging numerical results are presented for large-scale nonlinear multicommodity network flow problems.
Dostawca treści:: RCIN - Repozytorium Cyfrowe Instytutów Naukowych

Książka

Skocz do pozycji: 2.

Tytuł:: Lagrangian Relaxation via Ballstep Subgradient Methods
Raport Badawczy = Research Report ; RB/50/2005
Autorzy:: Kiwiel, Krzysztof
Lindberg, Per
Larsson, Torbjörn
Wydawca:: Instytut Badań Systemowych. Polska Akademia Nauk
Systems Research Institute. Polish Academy of Sciences
Powiązania:: Raport Badawczy = Research Report
Opis:: 19 stron ; 21 cm
19 pages ; 21 cm
The paper presents useful properties of ballstep subgradient methods for convex optimization that use level controls for estimating the optimal value. Augmented with simple averaging schemes, they asymptotically find objective and constraint subgradients involved in optimality conditions. When applied to Lagrangian relaxation of convex programs, they find both primal and dual solutions, and have practicable stopping criteria. Up till now, similar results have only been known for proximal bundle methods, and for subgradient methods with divergent series stepsizes, whose convergence can be slow. Encouraging numerical results are presented for large-scale nonlinear multicommodity network flow problems.
Bibliografia s. 18-19
Bibliography p. 18-19
Dostawca treści:: RCIN - Repozytorium Cyfrowe Instytutów Naukowych

Książka

Skocz do pozycji: 3.

Tytuł:: Aproximal-Projection Bundle Method for Lagrangian Relaxation, Including Semidefine Programming
Raport Badawczy = Research Report ; RB/60/2006
Autorzy:: Kiwiel, Krzysztof
Wydawca:: Instytut Badań Systemowych. Polska Akademia Nauk
Systems Research Institute. Polish Academy of Sciences
Powiązania:: Raport Badawczy = Research Report
Opis:: Bibliografia s. 20
20 pages ; 21 cm
The paper presents a proximal bundle method for minimizing a convex function f over a convex set C. It requires evaluating f and its subgradients with a fixed but possibly unknown accuracy ε> 0. Each iteration involves solving an unconstrained proximal subproblem and projecting a certain point onto C. The method asymptotically finds points that are ε-optimal. In Lagrangian relaxation of convex programs, it allows for ε-accurate solutions of Lagrangian subproblems and finds ε-optimal primal solutions. For semidefinite programming problems, it extends the highly successful spectral bundle method to the case of inexact eigenvalue computations.
20 stron ; 21 cm
Bibliography p. 20
Dostawca treści:: RCIN - Repozytorium Cyfrowe Instytutów Naukowych

Książka

Skocz do pozycji: 4.

Tytuł:: Aproximal-Projection Bundle Method for Lagrangian Relaxation, Including Semidefinite Programming
Raport Badawczy = Research Report ; RB/49/2005
Autorzy:: Kiwiel, Krzysztof
Wydawca:: Instytut Badań Systemowych. Polska Akademia Nauk
Systems Research Institute. Polish Academy of Sciences
Powiązania:: Raport Badawczy = Research Report
Opis:: Bibliography p. 19-20
20 pages ; 21 cm
The paper presents a proximal bundle method for minimizing a convex function f over a convex set C. It requires evaluating f and its subgradients with a fixed but possibly unknown accuracy ε> 0. Each iteration involves solving an unconstrained proximal subproblem, and projecting a certain point onto C. The method asymptotically finds points that are ε-optimal. In Lagrangian relaxation of convex programs, it allows for ε-accurate solutions of Lagrangian subproblems, and finds ε-optimal primal solutions. For semidefinite programming problems, it extends the highly successful spectral bundle method to the case of inexact eigenvalue computations.
Bibliografia s. 19-20
20 stron ; 21 cm
Dostawca treści:: RCIN - Repozytorium Cyfrowe Instytutów Naukowych

Książka

Skocz do pozycji: 5.

Tytuł:: A proximal bundle method with approximate subgradient linearizations
Raport Badawczy = Research Report ; RB/67/2003
Autorzy:: Kiwiel, Krzysztof
Wydawca:: Instytut Badań Systemowych. Polska Akademia Nauk
Systems Research Institute. Polish Academy of Sciences
Powiązania:: Raport Badawczy = Research Report
Opis:: 18 pages ; 21 cm
The paper presents a proximal bundle method for minimizing a convex function f over a closed convex set. It only requires evaluating f and its subgradients with an accuracy ε>0, which is fixed but possibly unknown. It asymptotically finds points that are ε-optimal. When applied to Lagrangian relaxation, it allows for ε-accurate solutions of Lagrangian subproblems, and finds ε-optimal solutions of convex programs.
Bibliography p. 17-18
18 stron ; 21 cm
Bibliografia s. 17-18
Dostawca treści:: RCIN - Repozytorium Cyfrowe Instytutów Naukowych

Książka

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