Národní úložiště šedé literatury Nalezeno 129 záznamů.  1 - 10dalšíkonec  přejít na záznam: Hledání trvalo 0.00 vteřin. 
Two limited-memory optimization methods with minimum violation of the previous quasi-Newton equations
Vlček, Jan ; Lukšan, Ladislav
Limited-memory variable metric methods based on the well-known BFGS update are widely used for large scale optimization. The block version of the BFGS update, derived by Schnabel (1983), Hu and Storey (1991) and Vlček and Lukšan (2019), satisfies the quasi-Newton equations with all used difference vectors and for quadratic objective functions gives the best improvement of convergence in some sense, but the corresponding direction vectors are not descent directions generally. To guarantee the descent property of direction vectors and simultaneously violate the quasi-Newton equations as little as possible in some sense, two methods based on the block BFGS update are proposed. They can be advantageously combined with methods based on vector corrections for conjugacy (Vlček and Lukšan, 2015). Global convergence of the proposed algorithm is established for convex and sufficiently smooth functions. Numerical experiments demonstrate the efficiency of the new methods.
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Hybrid Methods for Nonlinear Least Squares Problems
Lukšan, Ladislav ; Matonoha, Ctirad ; Vlček, Jan
This contribution contains a description and analysis of effective methods for minimization of the nonlinear least squares function F(x) = (1=2)fT (x)f(x), where x ∈ Rn and f ∈ Rm, together with extensive computational tests and comparisons of the introduced methods. All hybrid methods are described in detail and their global convergence is proved in a unified way. Some proofs concerning trust region methods, which are difficult to find in the literature, are also added. In particular, the report contains an analysis of a new simple hybrid method with Jacobian corrections (Section 8) and an investigation of the simple hybrid method for sparse least squares problems proposed previously in [33] (Section 14).
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Application of the Infinitely Many Times Repeated BNS Update and Conjugate Directions to Limited-Memory Optimization Methods
Vlček, Jan ; Lukšan, Ladislav
To improve the performance of the L-BFGS method for large scale unconstrained optimization, repeating of some BFGS updates was proposed. Since this can be time consuming, the extra updates need to be selected carefully. We show that groups of these updates can be repeated infinitely many times under some conditions, without a noticeable increase of the computational time. The limit update is a block BFGS update. It can be obtained by solving of some Lyapunov matrix equation whose order can be decreased by application of vector corrections for conjugacy. Global convergence of the proposed algorithm is established for convex and sufficiently smooth functions. Numerical results indicate the efficiency of the new method.
Horský hotel
Vlček, Jan ; Pilný, Ondřej (oponent) ; Berková, Petra (vedoucí práce)
Cílem diplomové práce je návrh Horského hotelu v obci Rokytnice nad Jizerou. Objekt je umístěn na svažité parcele nacházející se v turisticky a lyžařsky atraktivní oblasti Krkonoš. Horský hotel je čtyřpodlažní, podsklepený. V prvním nadzemím podlaží se nachází restaurace s terasou, kuchyně, zázemí hotelu. Ve druhém a třetím nadzemním podlaží jsou umístěny pokoje pro hosty a pokoj zaměstnance hotelu. V podzemním podlaží je umístěn wellness, technické zázemí a hromadná garáž. Nosnou konstrukci objektu tvoří železobetonové monolitické příčné rámy s výplňovým zdivem z keramických tvárnic.
A Hybrid Method for Nonlinear Least Squares that Uses Quasi-Newton Updates Applied to an Approximation of the Jacobian Matrix
Lukšan, Ladislav ; Vlček, Jan
In this contribution, we propose a new hybrid method for minimization of nonlinear least squares. This method is based on quasi-Newton updates, applied to an approximation A of the Jacobian matrix J, such that AT f = JT f. This property allows us to solve a linear least squares problem, minimizing ∥Ad+f∥ instead of solving the normal equation ATAd+JT f = 0, where d ∈ Rn is the required direction vector. Computational experiments confirm the efficiency of the new method.
Problems for Nonlinear Least Squares and Nonlinear Equations
Lukšan, Ladislav ; Matonoha, Ctirad ; Vlček, Jan
This report contains a description of subroutines which can be used for testing large-scale optimization codes. These subroutines can easily be obtained from the web page http://www.cs.cas.cz/~luksan/test.html. Furthermore, all test problems contained in these subroutines are presented in the analytic form.
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Sparse Test Problems for Nonlinear Least Squares
Lukšan, Ladislav ; Matonoha, Ctirad ; Vlček, Jan
This report contains a description of subroutines which can be used for testing large-scale optimization codes. These subroutines can easily be obtained from the web page http://www.cs.cas.cz/~luksan/test.html. Furthermore, all test problems contained in these subroutines are presented in the analytic form.
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UFO 2017. Interactive System for Universal Functional Optimization
Lukšan, Ladislav ; Tůma, Miroslav ; Matonoha, Ctirad ; Vlček, Jan ; Ramešová, Nina ; Šiška, M. ; Hartman, J.
This report contains a description of the interactive system for universal functional optimization UFO, version 2017. This version contains interfaces to the MATLAB and SCILAB graphics environments.

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