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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F09%3A00323060%21RIV09-AV0-67985556
rdf:type
n8:Vysledek skos:Concept
dcterms:description
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. 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. 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.
dcterms:title
Sekvenční algoritmus pro konvexní semidefinití programování aplikovaný na volnou optimalizaci materiálu A Sequential Convex Semidefinite Programming Algorithm for Multiple-Load Free Material Optimization A Sequential Convex Semidefinite Programming Algorithm for Multiple-Load Free Material Optimization
skos:prefLabel
A Sequential Convex Semidefinite Programming Algorithm for Multiple-Load Free Material Optimization Sekvenční algoritmus pro konvexní semidefinití programování aplikovaný na volnou optimalizaci materiálu A Sequential Convex Semidefinite Programming Algorithm for Multiple-Load Free Material Optimization
skos:notation
RIV/67985556:_____/09:00323060!RIV09-AV0-67985556
n3:aktivita
n14:Z n14:P
n3:aktivity
P(IAA1075402), Z(AV0Z10750506)
n3:cisloPeriodika
1
n3:dodaniDat
n10:2009
n3:domaciTvurceVysledku
n11:9094652
n3:druhVysledku
n17:J
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n12:predkladatel
n3:idSjednocenehoVysledku
301573
n3:idVysledku
RIV/67985556:_____/09:00323060
n3:jazykVysledku
n6:eng
n3:klicovaSlova
structural optimization; material optimization; semidefinite programming; sequential convex programming
n3:klicoveSlovo
n4:material%20optimization n4:sequential%20convex%20programming n4:structural%20optimization n4:semidefinite%20programming
n3:kodStatuVydavatele
US - Spojené státy americké
n3:kontrolniKodProRIV
[B19FACF2A2C1]
n3:nazevZdroje
SIAM Journal on Optimization
n3:obor
n13:BA
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
3
n3:projekt
n7:IAA1075402
n3:rokUplatneniVysledku
n10:2009
n3:svazekPeriodika
20
n3:tvurceVysledku
Leugering, G. Stingl, M. Kočvara, Michal
n3:zamer
n18:AV0Z10750506
s:issn
1052-6234
s:numberOfPages
26