Minimizing quadratic functions with separable quadratic constraints

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dc.contributor.author Kučera, Radek
dc.date.accessioned 2007-07-20T08:31:39Z
dc.date.available 2007-07-20T08:31:39Z
dc.date.issued 2007
dc.identifier.citation Optimization methods and software. 2007, vol. 22, issue 3, p. 453-467. en
dc.identifier.issn 1055-6788
dc.identifier.issn 1029-4937
dc.identifier.uri http://hdl.handle.net/10084/61012
dc.language.iso en en
dc.publisher Taylor & Francis en
dc.relation.ispartofseries Optimization methods and software en
dc.relation.uri http://dx.doi.org/10.1080/10556780600609246 en
dc.subject quadratic function en
dc.subject separable quadratic constraints en
dc.subject active set en
dc.subject convergence en
dc.subject conjugate gradient method en
dc.subject adaptive precision control en
dc.title Minimizing quadratic functions with separable quadratic constraints en
dc.type article en
dc.identifier.location Není ve fondu ÚK en
dc.description.abstract-en This article deals with minimizing quadratic functions with a special form of quadratic constraints that arise in 3D contact problems of linear elasticity with isotropic friction [Haslinger, J., Kučera, R. and Dostál, Z., 2004, An algorithm for the numerical realization of 3D contact problems with Coulomb friction. Journal of Computational and Applied Mathematics, 164/165, 387-408.]. The proposed algorithm combines the active set method with the conjugate gradient method. Its general scheme is similar to the algorithms of Polyak's type that solve the quadratic programming problems with simple bounds. As the algorithm does not terminate in a finite number of steps, the convergence is proved. The implementation uses an adaptive precision control of the conjugate gradient loops. Numerical experiments demonstrate the computational efficiency of the method. en
dc.identifier.doi 10.1080/10556780600609246
dc.identifier.wos 000246622500005

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