| bibtype |
J -
Journal Article
|
| ARLID |
0323060 |
| utime |
20240103191507.9 |
| mtime |
20090417235959.9 |
| DOI |
10.1137/070711281 |
| title
(primary) (eng) |
A Sequential Convex Semidefinite Programming Algorithm for Multiple-Load Free Material Optimization |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0255073 |
| ISSN |
1052-6234 |
| title
|
SIAM Journal on Optimization |
| volume_id |
20 |
| volume |
1 (2009) |
| page_num |
130-155 |
| publisher |
| name |
SIAM Society for Industrial and Applied Mathematics |
|
|
| title
(cze) |
Sekvenční algoritmus pro konvexní semidefinití programování aplikovaný na volnou optimalizaci materiálu |
| keyword |
structural optimization |
| keyword |
material optimization |
| keyword |
semidefinite programming |
| keyword |
sequential convex programming |
| author
(primary) |
| ARLID |
cav_un_auth*0021060 |
| name1 |
Stingl |
| name2 |
M. |
| country |
DE |
|
| author
|
| ARLID |
cav_un_auth*0101131 |
| name1 |
Kočvara |
| name2 |
Michal |
| institution |
UTIA-B |
| full_dept |
Department of Decision Making Theory |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0249570 |
| name1 |
Leugering |
| name2 |
G. |
| country |
DE |
|
| cas_special |
| project |
| project_id |
IAA1075402 |
| agency |
GA AV ČR |
| ARLID |
cav_un_auth*0012788 |
|
| project |
| project_id |
EU-FP6-30717 |
| agency |
commision EU |
| country |
XE |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
A new method for the efficient solution of a class of convex semidefinite programming problems is introduced. The method extends the sequential convex programming (SCP) concept to optimization problems with matrix variables. The basic idea of the new method is to approximate the original optimization problem by a sequence of subproblems, in which nonlinear functions (defined in matrix variables) are approximated by block separable convex functions. The subproblems are semidefinite programs with a favorable structure which can be efficiently solved by existing SDP software. The new method is shown to be globally convergent. The article is concluded by a series of numerical experiments with free material optimization problems demonstrating the effectiveness of the generalized SCP approach. |
| abstract
(cze) |
Je uvedena nová metoda pro účinné řešení třídy konvexních semidefinitních programů. Tato metoda rozšiřuje sekvenční konvexní programování (SCP) na optimalizační problémy s maticovými proměnnými. Základní myšlenkou metody je aproximovat původní optimalizační problém posloupností subproblémů, ve kterých jsou nelineární funkce (v proměnných maticích) aproximovány konvexními blokově separabilními funkcemi. V subproblémech jsou semidefinitní programy s příznivou strukturou, které mohou být účinně vyřešeny stávajícím SDP softwarem. Je ukázáno, že metoda je globálně konvergentní. |
| reportyear |
2009 |
| RIV |
BA |
| permalink |
http://hdl.handle.net/11104/0171136 |
| mrcbT16-f |
2.388 |
| mrcbT16-g |
0.18 |
| mrcbT16-h |
9.1 |
| mrcbT16-i |
0.01165 |
| mrcbT16-j |
1.542 |
| mrcbT16-k |
3283 |
| mrcbT16-l |
50 |
| arlyear |
2009 |
| mrcbU63 |
cav_un_epca*0255073 SIAM Journal on Optimization 1052-6234 1095-7189 Roč. 20 č. 1 2009 130 155 SIAM Society for Industrial and Applied Mathematics |
|