• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 117
  • 72
  • 15
  • 6
  • 4
  • 4
  • 4
  • 3
  • 2
  • 2
  • 1
  • 1
  • 1
  • 1
  • 1
  • Tagged with
  • 255
  • 255
  • 129
  • 112
  • 108
  • 99
  • 56
  • 50
  • 40
  • 38
  • 35
  • 33
  • 30
  • 29
  • 27
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

Algorithms for the solution of the quadratic programming problem

Vankova, Martina January 2004 (has links)
The purpose of this dissertation was to provide a review of the theory of Optimization, in particular quadratic programming, and the algorithms suitable for solving both convex and non-convex quadratic programming problems. Optimization problems arise in a wide variety of fields and many can be effectively modeled with linear equations. However, there are problems for which linear models are not sufficient thus creating a need for non-linear systems. This dissertation includes a literature study of the formal theory necessary for understanding optimization and an investigation of the algorithms available for solving a special class of the non-linear programming problem, namely the quadratic programming problem. It was not the intention of this dissertation to discuss all possible algorithms for solving the quadratic programming problem, therefore certain algorithms for convex and non-convex quadratic programming problems were selected for a detailed discussion in the dissertation. Some of the algorithms were selected arbitrarily, because limited information was available comparing the efficiency of the various algorithms. Algorithms available for solving general non-linear programming problems were also included and briefly discussed as they can be used to solve quadratic programming problems. A number of algorithms were then selected for evaluation, depending on the frequency of use in practice and the availability of software implementing these algorithms. The evaluation included a theoretical and quantitative comparison of the algorithms. The quantitative results were analyzed and discussed and it was shown that the results supported the theoretical comparison. It was also shown that it is difficult to conclude that one algorithm is better than another as the efficiency of an algorithm greatly depends on the size of the problem, the complexity of an algorithm and many other implementation issues. Optimization problems arise continuously in a wide range of fields and thus create the need for effective methods of solving them. This dissertation provides the fundamental theory necessary for the understanding of optimization problems, with particular reference to quadratic programming problems and the algorithms that solve such problems. Keywords: Quadratic Programming, Quadratic Programming Algorithms, Optimization, Non-linear Programming, Convex, Non-convex.

Algorithms for short-term and periodic process scheduling and rescheduling

Schilling, Gordian Hansjoerg January 1998 (has links)
No description available.


Tsao, Lu-Ping, 1959- January 1986 (has links)
No description available.

Filter-Trust-Region Methods for Nonlinear Optimization

Sainvitu, Caroline 17 April 2007 (has links)
This work is concerned with the theoretical study and the implementation of algorithms for solving two particular types of nonlinear optimization problems, namely unconstrained and simple-bound constrained optimization problems. For unconstrained optimization, we develop a new algorithm which uses a filter technique and a trust-region method in order to enforce global convergence and to improve the efficiency of traditional approaches. We also analyze the effect of approximate first and second derivatives on the performance of the filter-trust-region algorithm. We next extend our algorithm to simple-bound constrained optimization problems by combining these ideas with a gradient-projection method. Numerical results follow the proposed methods and indicate that they are competitive with more classical trust-region algorithms.

Convergence of a gradient projection method

January 1982 (has links)
Eli M. Gafni, Dimitri P. Bertsekas. / "May 1982" / Bibliography: leaf 12. / "Grant NSF ENG-79-106332"

Analyse und Anwendungen von Quotientenprogrammen e. Beitr. zur Planung mit Hilfe d. nichtlinearen Programmierung /

Schaible, Siegfried. January 1978 (has links)
Habilitationsschrift--Cologne, 1977. / Includes bibliographical references (p. [238]-259).

OQGRG a multi-start algorithm for global solution of nonlinear and mixed integer programs /

Ugray, Zsolt Gyula. January 2001 (has links) (PDF)
Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from UMI Company.

Binary image restoration by positive semidefinite programming and signomial programming

Shen, Yijiang. January 2007 (has links)
Thesis (M. Phil.)--University of Hong Kong, 2008. / Also available in print.

Optimal transmitter placement in wireless mesh networks

Nicholas, Paul J. January 2009 (has links) (PDF)
Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2009. / Thesis Advisor(s): Alderson, David. "June 2009." Author(s) subject terms: Wireless Mesh Networks, Humanitarian Assistance, Disaster Relief, Distributed Operations, Enhanced Company Operations, Network Design, Nonlinear Programming, Terrain Integrated Rough Earth Model, TIREM, Hata COST-231, Simultaneous Routing and Resource Allocation, Dividing Rectangles, DIRECT, Access Points, Access Point Placement, C++ Description based on title screen as viewed on July 13, 2009. Includes bibliographical references (p. 119-122). Also available in print.

Control and Optimization of Track Coverage in Underwater Sensor Networks

Baumgartner, Kelli A. Crews. January 2007 (has links)
Thesis (Ph. D.)--Duke University, 2007.

Page generated in 0.2009 seconds