Дисертації з теми "Quadratic programmin"
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Lau, Karen Karman School of Mathematics UNSW. "Multistage quadratic stochastic programming." Awarded by:University of New South Wales. School of Mathematics, 1999. http://handle.unsw.edu.au/1959.4/32672.
Повний текст джерелаIlyes, Amy Louise. "Using linear programming to solve convex quadratic programming problems." Case Western Reserve University School of Graduate Studies / OhioLINK, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=case1056644216.
Повний текст джерелаGrainger, Daniel John. "Contributions to Quadratic 0 -1 Programming." Thesis, Lancaster University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.518188.
Повний текст джерелаWang, Xianzhi. "Resolution of Ties in Parametric Quadratic Programming." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/1199.
Повний текст джерелаByrne, Susan Jane. "Quadratic programming using complementarity and orthogonal factorization." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/8893.
Повний текст джерелаMorales-Perez, Jose Luis. "Computational methods for large-scale quadratic programming." Thesis, Imperial College London, 1993. http://hdl.handle.net/10044/1/7511.
Повний текст джерелаAxehill, Daniel. "Integer quadratic programming for control and communcation /." Linköping : Department of Electrical Engineering, Linköping University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10642.
Повний текст джерелаJakee, Khan Md Kamall. "Computational convex analysis using parametric quadratic programming." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45182.
Повний текст джерелаAxehill, Daniel. "Integer Quadratic Programming for Control and Communication." Doctoral thesis, Linköpings universitet, Reglerteknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10642.
Повний текст джерелаThis material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the Linköping University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this material, you agree to all provisions of the copyright laws protecting it.
Ahlbom, Daniel. "Quadratic Programming Models in Strategic Sourcing Optimization." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-334227.
Повний текст джерелаLopez, Rafaël. "Stochastic quadratic knapsack problems and semidefinite programming." Paris 11, 2009. http://www.theses.fr/2009PA112283.
Повний текст джерелаIn this thesis, we study stochastic quadratic knapsack problems and applications of Semidefinite Programming for a telecommunication problem and for an experimental study of the MaxCut and CDMA problems. The first part of this thesis gives the prelimary notions and results necessary to develop and understand the contents of this thesis. The second part is the study of the stochastic quadratic knapsack problem, for which we develop a new formulation, using recourse (two-stage) and probabilistic contraints. We give multiple variants of this formulation. We propose various relaxations of this problems, based on the linear relaxation and on SDP. We show that SDP gives significantly better bounds than linear relaxation. Finally, we develop an approximation heuristic based on the result of the linear relaxation and of the second SDP relaxation, and give details of their respective performances. The third part of this thesis is dedicated to applications of SDP on pratical problems. The first application we study is a telecommunication problem : the multiuser detection problem in CDMA. We develop a new algorithm combining SDP and a VNS meta-heuristic to obtain a better signal quality. We detail the experimental results of our method and of other SDP based methods. The second application is an experimental comparison of various relaxations for the MaxCut problem and the CDMA problem. We detail the performances of Lagrangian and SDP relaxations compared to linear relaxation, and to the spectral decomposition in the CDMA case
Cheng, Chun-Min. "Use of linear quadratic and quadratic programming methods in model-based process control /." Thesis, Connect to this title online; UW restricted, 1986. http://hdl.handle.net/1773/9814.
Повний текст джерелаSharma, Vivek Narain. "Linear programming and quadratic programming approach for graduation in fuzzy environment." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ57577.pdf.
Повний текст джерелаP, Van Voorhis Timothy. "The quadratically constrained quadratic program." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/23379.
Повний текст джерелаPinheiro, Ricardo Bento Nogueira [UNESP]. "Um método previsor-corretor primal-dual de pontos interiores barreira logarítmica modificada, com estratégias de convergência global e de ajuste cúbico, para problemas de programação não-linear e não-convexa." Universidade Estadual Paulista (UNESP), 2012. http://hdl.handle.net/11449/87189.
Повний текст джерелаCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Neste trabalho apresentamos o método previsor-corretor primal-dual de pontos interiores, com barreira logarítmica modificada e estratégia de ajuste cúbico (MPIBLM-EX) e o método previsor-corretor primal-dual de pontos interiores, com barreira logarítmica modificada, com estratégias de ajuste cúbico e de convergência global (MPIBLMCG-EX). Na definição do algoritmo proposto, a função barreira logarítmica modificada auxilia o método em sua inicialização com pontos inviáveis. Porém, a inviabilidade pode ocorrer em pontos tais que o logaritmo não está definido, consequentemente, isso implica na não existência de função barreira logarítmica modificada. Para suprir essa dificuldade um polinômio cúbico ajustado ao logaritmo, que preserva as derivadas de primeira e segunda do mestre definido a partir de um ponto da região ampliada ao método previsor-corretor primal-dual de pontos interiores com barreira logarítmica modificada (MPIBML); no processo previsor são realizadas atualizações do parâmetro de barreira nos resíduos das restrições de complementaridade, considerando aproximações de primeira ordem do sistema de direções de busca, enquanto que no procedimento corretor, incluímos os termos quadráticos não-lineares dos resíduos citados, que foram desprezados no procedimento previsor. Considerando também a estratégia de convergência global para o MPIBLM-EX, a qual utiliza uma variante do método de Levenberg-Marquardt para ajustar a matriz dual normal da função lagrangiana, caso esta não seja definida positiva. A matriz dual normal é redefinida para as restrições primais de igualdade, de desigualdade e para as variáveis canalizadas, incorporando variáveis duais e matrizes diagonais relativas às restrições de complementariade. Desse estudo, o MPIBLM-EX é transformado no MPIBLMCG-EX e mostramos...
This work presents a predictor primal-dual interior point method with modified log-barrier and third order extrapolation strategy (IPMLBM-EX) and also and extension of this method with the inclusion of the global convergence strategy (IPMLBGCM-EX). In the definition of the proposed algorithm, the modified log-barrier function helps the method initialize with infeasible points. However, infeasibility may occur for some point where the logarithm is not defined. The implicates in non-existence of the modified log-barrier function. To cope with such as problem, a cubic polynomial function is adjusted to the logarithmic function. Sucha polynomial function preserves first and second order derivatives in certain point defined in the extended region. This function is applied to the predictor-corretor primal-dual interior point method with modified log-barrier function. In the predictor procedure, the barrier parameter is updated in the complementarity conditions considering first-order approximations of the search direction, while the corrector procedure includes the nonlinear quadratic terms of the mentioned residuals, which were neglected in the predictor procedure. We also consider the global convergence strategy for the method, which uses a variant of the Levenberg-Marquardt method to update the normal dual matrix of the Langrangian function, should it fail to be positively defined. In this case, this matrix is redefined for equality primal constraints, bounded inequality primal constraints and bounded variables, incorporating dual variables and diagonal matrices of the complementarity constraints. From such studies, the IPMLBM-EX method is extended to include the global convergence strategy (IPMLBGCM-EX). We have show that both methods are projected gradient methods. An implementation performed with Matlab 6.1 has shown the... (Complete abstract click electronic access below)
Pinheiro, Ricardo Bento Nogueira. "Um método previsor-corretor primal-dual de pontos interiores barreira logarítmica modificada, com estratégias de convergência global e de ajuste cúbico, para problemas de programação não-linear e não-convexa /." Bauru : [s.n.], 2012. http://hdl.handle.net/11449/87189.
Повний текст джерелаBanca: Edilaine Martins Soler
Banca: Leonardo Nepomuceno
Resumo: Neste trabalho apresentamos o método previsor-corretor primal-dual de pontos interiores, com barreira logarítmica modificada e estratégia de ajuste cúbico (MPIBLM-EX) e o método previsor-corretor primal-dual de pontos interiores, com barreira logarítmica modificada, com estratégias de ajuste cúbico e de convergência global (MPIBLMCG-EX). Na definição do algoritmo proposto, a função barreira logarítmica modificada auxilia o método em sua inicialização com pontos inviáveis. Porém, a inviabilidade pode ocorrer em pontos tais que o logaritmo não está definido, consequentemente, isso implica na não existência de função barreira logarítmica modificada. Para suprir essa dificuldade um polinômio cúbico ajustado ao logaritmo, que preserva as derivadas de primeira e segunda do mestre definido a partir de um ponto da região ampliada ao método previsor-corretor primal-dual de pontos interiores com barreira logarítmica modificada (MPIBML); no processo previsor são realizadas atualizações do parâmetro de barreira nos resíduos das restrições de complementaridade, considerando aproximações de primeira ordem do sistema de direções de busca, enquanto que no procedimento corretor, incluímos os termos quadráticos não-lineares dos resíduos citados, que foram desprezados no procedimento previsor. Considerando também a estratégia de convergência global para o MPIBLM-EX, a qual utiliza uma variante do método de Levenberg-Marquardt para ajustar a matriz dual normal da função lagrangiana, caso esta não seja definida positiva. A matriz dual normal é redefinida para as restrições primais de igualdade, de desigualdade e para as variáveis canalizadas, incorporando variáveis duais e matrizes diagonais relativas às restrições de complementariade. Desse estudo, o MPIBLM-EX é transformado no MPIBLMCG-EX e mostramos... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: This work presents a predictor primal-dual interior point method with modified log-barrier and third order extrapolation strategy (IPMLBM-EX) and also and extension of this method with the inclusion of the global convergence strategy (IPMLBGCM-EX). In the definition of the proposed algorithm, the modified log-barrier function helps the method initialize with infeasible points. However, infeasibility may occur for some point where the logarithm is not defined. The implicates in non-existence of the modified log-barrier function. To cope with such as problem, a cubic polynomial function is adjusted to the logarithmic function. Sucha polynomial function preserves first and second order derivatives in certain point defined in the extended region. This function is applied to the predictor-corretor primal-dual interior point method with modified log-barrier function. In the predictor procedure, the barrier parameter is updated in the complementarity conditions considering first-order approximations of the search direction, while the corrector procedure includes the nonlinear quadratic terms of the mentioned residuals, which were neglected in the predictor procedure. We also consider the global convergence strategy for the method, which uses a variant of the Levenberg-Marquardt method to update the normal dual matrix of the Langrangian function, should it fail to be positively defined. In this case, this matrix is redefined for equality primal constraints, bounded inequality primal constraints and bounded variables, incorporating dual variables and diagonal matrices of the complementarity constraints. From such studies, the IPMLBM-EX method is extended to include the global convergence strategy (IPMLBGCM-EX). We have show that both methods are projected gradient methods. An implementation performed with Matlab 6.1 has shown the... (Complete abstract click electronic access below)
Mestre
Tao, Ye. "Optimal power flow via quadratic modeling." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/45766.
Повний текст джерелаSzularz, Marek. "Quadratic programming with constant norm with parallel applications." Thesis, Kingston University, 1991. http://eprints.kingston.ac.uk/20556/.
Повний текст джерелаBettiol, Enrico. "Column generation methods for quadratic mixed binary programming." Thesis, Paris 13, 2019. http://www.theses.fr/2019PA131073.
Повний текст джерелаNon linear programming problems. There are several solution methods in literature for these problems, which are, however, not always efficient in general, in particular for large scale problems. Decomposition strategies such as Column Generation have been developed in order to substitute the original problem with a sequence of more tractable ones. One of the most known of these techniques is Dantzig-Wolfe Decomposition: it has been developed for linear problems and it consists in solving a sequence of subproblems, called respectively master and pricing programs, which leads to the optimum. This method can be extended to convex non linear problems and a classic example of this, which can be seen also as a generalization of the Frank-Wolfe algorithm, is Simplicial Decomposition(SD).In this thesis we discuss decomposition algorithms for solving quadratic optimization problems. In particular, we start with quadratic convex problems, both continuous and mixed binary. Then we tackle the more general class of binary quadratically constrained, quadratic problems. In the first part, we concentrate on SD based-methods for continuous, convex quadratic programming. We introduce new features in the algorithms, for both the master and the pricing problems of the decomposition, and provide results for a wide set of instances, showing that our algorithm is really efficient if compared to the state-of-the-art solver Cplex. This first work is accepted for publication in the journal Computational Optimization and Applications.We then extend the SD-based algorithm to mixed binary convex quadratic problems;we embed the continuous algorithm in a branch and bound scheme that makes us able to exploit some properties of our framework. In this context again we obtain results which show that in some sets of instances this algorithm is still more efficient than Cplex,even with a very simple branch and bound algorithm. This work is in preparation for submission to a journal. In the second part of the thesis, we deal with a more general class of problems, that is quadratically constrained, quadratic problems, where the constraints can be quadratic and both the objective function and the constraints can be non convex. For this class of problems we extend the formulation to the matrix space of the products of variables; we study an algorithm based on Dantzig-Wolfe Decomposition that exploits a relaxation on the Boolean Quadric Polytope (BQP), which is strictly contained in the Completely Positive cone and hence in the cone of positive semi definite (PSD) matrices. This is a constructive algorithm to solve the BQP relaxation of a binary problem an dwe obtain promising results for the root node bound for some quadratic problems. We compare our results with those obtained by the Semi definite relaxation of the ad-hocsolver BiqCrunch. We also show that, for linearly constrained quadratic problems, our relaxation can provide the integer optimum, under certain assumptions. We further study block decomposed matrices and provide results on the so-called BQP-completion problem ; these results are connected to those of PSD and CPP matrices. We show that, given a BQP matrix with some unspecified elements, it can be completed to a full BQP matrix under some assumptions on the positions of the specified elements. This result is related to optimization problems. We propose a BQP-relaxation based on the block structure of the problem. We prove that it provides a lower bound for the previously introduced relaxation, and that in some cases the two formulations are equivalent. We also conjecture that the equivalence result holds if and only if its so-called specification graph is chordal. We provide computational results which show the improvement in the performance of the block-based relaxation, with respect to the unstructured relaxation, and which support our conjecture. This work is in preparation for submission to a journal
Boljunčić, Jadranka. "Quadratic programming : quantitative analysis and polynomial running time algorithms." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/27532.
Повний текст джерелаz̅ - x̅
∞≤n∆(A) where n is the number of variables and ∆(A) is the largest absolute sub-determinant of the integer constraint matrix A . We have further shown that for any feasible solution z, which is not optimal for the separable quadratic integer programming problem, there exists a feasible solution z̅ having greater objective function value and with
z - z̅
∞≤n∆(A). Under some additional assumptions the distance between a pair of optimal solutions to the integer quadratic programming problem with right hand side vectors b and b', respectively, depends linearly on
b — b'
₁. The extension to the mixed-integer nonseparable quadratic case is also given. Some sensitivity analysis results for nonlinear integer programming problems are given. We assume that the nonlinear 0 — 1 problem was solved by implicit enumeration and that some small changes have been made in the right hand side or objective function coefficients. We then established what additional information to keep in the implicit enumeration tree, when solving the original problem, in order to provide us with bounds on the optimal value of a perturbed problem. Also, suppose that after solving the original problem to optimality the problem was enlarged by introducing a new 0 — 1 variable, say xn+1. We determined a lower bound on the added objective function coefficients for which the new integer variable xn+1 remains at zero level in the optimal solution for the modified integer nonlinear program. We discuss the extensions to the mixed-integer case as well as to the case when integer variables are not restricted to be 0 or 1. The computational results for an example with quadratic objective function, linear constraints and 0—1 variables are provided. Finally, we have shown how to replace the objective function of a quadratic program with 0—1 variables ( by an integer objective function whose size is polynomially bounded by the number of variables) without changing the set of optimal solutions. This was done by making use of the algorithm given by Frank and Tardos (1985) which in turn uses the simultaneous approximation algorithm of Lenstra, Lenstra and Lovász (1982).
Business, Sauder School of
Graduate
Vankova, Martina. "Algorithms for the solution of the quadratic programming problem." Thesis, University of Port Elizabeth, 2004. http://hdl.handle.net/10948/348.
Повний текст джерелаBen, Daya Mohamed. "Barrier function algorithms for linear and convex quadratic programming." Diss., Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/25502.
Повний текст джерелаHelme, Marcia P., and Thomas L. Magnanti. "Designing Satellite Communication Networks by Zero-One Quadratic Programming." Massachusetts Institute of Technology, Operations Research Center, 1987. http://hdl.handle.net/1721.1/5376.
Повний текст джерелаAxehill, Daniel. "Applications of Integer Quadratic Programming in Control and Communication." Licentiate thesis, Linköping : Dept. of Electrical Engineering, Linköping University, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5263.
Повний текст джерелаTuncbilek, Cihan H. "Polynomial and indefinite quadratic programming problems: algorithms and applications." Diss., Virginia Tech, 1994. http://hdl.handle.net/10919/39040.
Повний текст джерелаPajic, Slobodan. "Sequential quadratic programming-based contingency constrained optimal power flow." Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-0430103-152758.
Повний текст джерелаSantos, Francisco Lucio dos Reis Borges Brito dos. "Optimal irrigation system selection: A multiperiod quadratic programming approach." Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/184980.
Повний текст джерелаEdwards, Teresa Dawn. "The box method for minimizing strictly convex functions over convex sets." Diss., Georgia Institute of Technology, 1990. http://hdl.handle.net/1853/30690.
Повний текст джерелаYue, Hongwei. "First-order affine scaling continuous method for convex quadratic programming." HKBU Institutional Repository, 2014. https://repository.hkbu.edu.hk/etd_oa/39.
Повний текст джерелаChen, Chung Long. "A class of successive quadratic programming methods for flowsheet optimisation." Thesis, Imperial College London, 1988. http://hdl.handle.net/10044/1/8462.
Повний текст джерелаBrooks, S. A. "A penalty/modified barrier method for large-scale quadratic programming." Thesis, University of Cambridge, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.596942.
Повний текст джерелаZoppke-Donaldson, Christine. "A tolerance-tube approach to sequential quadratic programming with applications." Thesis, University of Dundee, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.531437.
Повний текст джерелаNaik, Vihangkumar Vinaykumar. "Mixed-integer quadratic programming algorithms for embedded control and estimation." Thesis, IMT Alti Studi Lucca, 2018. http://e-theses.imtlucca.it/259/1/Naik_phdthesis.pdf.
Повний текст джерелаVandenbussche, Dieter. "Polyhedral approaches to solving nonconvex quadratic programs." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/23385.
Повний текст джерелаAdams, Warren Philip. "The mixed-integer bilinear programming problem with extensions to zero-one quadratic programs." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/74711.
Повний текст джерелаPh. D.
Celik, Gul. "Parameter Estimation In Generalized Partial Linear Models With Conic Quadratic Programming." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612531/index.pdf.
Повний текст джерелаSirovljevic, Jelena. "Incomplete factorization preconditioners for least squares and linear and quadratic programming." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/32071.
Повний текст джерелаScience, Faculty of
Computer Science, Department of
Graduate
Ellison, E. F. D. "Solution methods and applications of convex quadratic programming and its extensions." Thesis, Brunel University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436501.
Повний текст джерелаKisala, Thomas P. "Successive Quadratic Programming in sequential modular process flowsheet simulation and optimization." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/99554.
Повний текст джерелаMICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE.
Bibliography: leaves 244-248.
by Thomas Patrick Kisala.
Sc.D.
Hu, Sha S. M. Massachusetts Institute of Technology. "Semidefinite relaxation based branch-and-bound method for nonconvex quadratic programming." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/39217.
Повний текст джерелаIncludes bibliographical references (leaves 73-75).
In this thesis, we use a semidefinite relaxation based branch-and-bound method to solve nonconvex quadratic programming problems. Firstly, we show an interval branch-and-bound method to calculate the bounds for the minimum of bounded polynomials. Then we demonstrate four SDP relaxation methods to solve nonconvex Box constrained Quadratic Programming (BoxQP) problems and the comparison of the four methods. For some lower dimensional problems, SDP relaxation methods can achieve tight bounds for the BoxQP problem; whereas for higher dimensional cases (more than 20 dimensions), the bounds achieved by the four Semidefinite programming (SDP) relaxation methods are always loose. To achieve tight bounds for higher dimensional BoxQP problems, we combine the branch-and-bound method and SDP relaxation method to develop an SDP relaxation based branch-and-bound (SDPBB) method. We introduce a sensitivity analysis method for the branching process of SDPBB. This sensitivity analysis method can improve the convergence speed significantly.
(cont.) Compared to the interval branch-and-bound method and the global optimization software BARON, SDPBB can achieve better bounds and is also much more efficient. Additionally, we have developed a multisection algorithm for SDPBB and the multisection algorithm has been parallelized using Message Passing Interface (MPI). By parallelizing the program, we can significantly improve the speed of solving higher dimensional BoxQP problems.
by Sha Hu.
S.M.
Hernandez, Marli de Freitas Gomes. "Algorithms for large sparse constrained optimisation." Thesis, University of Hertfordshire, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.259626.
Повний текст джерелаOzmen, Ayse. "Robust Conic Quadratic Programming Applied To Quality Improvement -a Robustification Of Cmars." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612513/index.pdf.
Повний текст джерелаit is more model-based and employs continuous, actually, well-structured convex optimization which enables the use of Interior Point Methods and their codes such as MOSEK. In this study, we are generalizing the regression problem by including uncertainty in the model, especially, in the input data, too. CMARS, recently developed as an alternative method to MARS, is powerful in overcoming complex and heterogeneous data. However, for MARS and CMARS method, data are assumed to contain fixed variables. In fact, data include noise in both output and input variables. Consequently, optimization problem&rsquo
s solutions can show a remarkable sensitivity to perturbations in the parameters of the problem. In this study, we include the existence of uncertainty in the future scenarios into CMARS and robustify it with robust optimization which is dealt with data uncertainty. That kind of optimization was introduced by Aharon Ben-Tal and Arkadi Nemirovski, and used by Laurent El Ghaoui in the area of data mining. It incorporates various kinds of noise and perturbations into the programming problem. This robustification of CQP with robust optimization is compared with previous contributions that based on Tikhonov regularization, and with the traditional MARS method.
Salah, Maher Jawad Younis. "Optimum plastic design of structures by generalized inverse theory and quadratic programming." Thesis, Queen Mary, University of London, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337445.
Повний текст джерелаJung, Jin Hyuk. "Adaptive constraint reduction for convex quadratic programming and training support vector machines." College Park, Md. : University of Maryland, 2008. http://hdl.handle.net/1903/8020.
Повний текст джерелаThesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Paparistodemo, Marios. "Multinomial lattices and a quadratic programming approach for optimal replication in incomplete markets." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271650.
Повний текст джерелаKang, Kyehong. "A structured reduced sequential quadratic programming and its application to a shape design problem." Diss., Virginia Tech, 1994. http://hdl.handle.net/10919/38565.
Повний текст джерелаPh. D.
Rajgopal, P. "A flexible construction and improvement heuristic for the quadratic assignment problem." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/101253.
Повний текст джерелаM.S.
Okan, Osman Burak. "Merging quadratic programming with kernel smoothing for automated cluster expansions of complex lattice Hamiltonians." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/44383.
Повний текст джерелаIncludes bibliographical references (p. 46-48).
We present a general outline for automating cluster expansions of configurational energetics in systems with crystallographic order and well defined space group symmetry. The method presented herein combines constrained optimization techniques of positive-definitive quadratic forms with the mathematical tool of Tikhonov regularization (kernel smoothing) for automated expansions of an arbitrary general physical property without compromising the underlying physics. Throughout the thesis we treat formation energy as the fundamental physical observable to expand on since the predominant application of cluster expansions is the extraction of robust approximations for configurational energetics in alloys and oxides. We therefore present the implementational aspects of the novel algorithmic route on a challenging material system NaxCoO2 and reconstruct the corresponding GGA ground state line with arbitrary precision in the formation energy-configuration space. The mathematical arguments and proofs, although discussed for cases with arbitrary spin assignments and multiple candidate species for single site occupancy, are eventually formulated and illustrated for binary systems. Various numerical challanges and the way they are resolved in the framework of kernel smoothing are addressed in detail as well. However, the applicability of the procedure described herein is more universal and can be tailored to probe different observables without resorting to modifications in the algorithmic implementation or the fundemantal mathematical construction. The effectiveness in recovering correct physics shall than be solely tied to the presence of superposable nature (of the physical property of interest) of local atomic configurations or lackthereof.
by Osman Burak Okan.
S.M.
Cha, Kyungduck. "Cancer treatment optimization." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22604.
Повний текст джерелаCommittee Chair: Lee, Eva K.; Committee Member: Barnes, Earl; Committee Member: Hertel, Nolan E.; Committee Member: Johnson, Ellis; Committee Member: Monteiro, Renato D.C.
Theußl, Stefan, Florian Schwendinger, and Kurt Hornik. "ROI: An extensible R Optimization Infrastructure." WU Vienna University of Economics and Business, 2019. http://epub.wu.ac.at/5858/1/ROI_StatReport.pdf.
Повний текст джерелаSeries: Research Report Series / Department of Statistics and Mathematics