• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 30
  • 11
  • 4
  • 3
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • Tagged with
  • 54
  • 54
  • 20
  • 14
  • 11
  • 11
  • 10
  • 7
  • 6
  • 6
  • 6
  • 6
  • 6
  • 6
  • 5
  • 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.
1

Convex programming without constraint qualification : a study of Pareto optimality

Fraklin, Martin Gordon. January 1975 (has links)
No description available.
2

Decomposition methods for structured convex programming

Ha, Cu Duong. January 1980 (has links)
Thesis (Ph. D.)--University of Wisconsin--Madison, 1980. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 101-106).
3

Solving discrete minimax problems with constraints

Turner, Bella Tobie January 1976 (has links)
No description available.
4

A convex hull algorithm optimal for point sets in even dimensions

Seidel, Raimund January 1981 (has links)
Finding the convex hull of a finite set of points is important not only for practical applications but also for theoretical reasons: a number of geometrical problems, such as constructing Voronoi diagrams or intersecting hyperspheres, can be reduced to the convex hull problem, and a fast convex hull algorithm yields fast algorithms for these other problems. This thesis deals with the problem of constructing the convex hull of a finite point set in R . Mathematical properties of convex hulls are developed, in particular, their facial structure, their representation, bounds on the number of faces, and the concept of duality. The main result of this thesis is an O(nlogn + n[(d+1)/2]) algorithm for the construction of the convex hull of n points in Rd. It is shown that this algorithm is worst case optimal for even d≥2. / Science, Faculty of / Computer Science, Department of / Graduate
5

Continuous methods for convex programming and convex semidefinite programming

Qian, Xun 07 August 2017 (has links)
In this thesis, we study several interior point continuous trajectories for linearly constrained convex programming (CP) and convex semidefinite programming (SDP). The continuous trajectories are characterized as the solution trajectories of corresponding ordinary differential equation (ODE) systems. All our ODE systems are closely related to interior point methods.. First, we propose and analyze three continuous trajectories, which are the solutions of three ODE systems for linearly constrained convex programming. The three ODE systems are formulated based on an variant of the affine scaling direction, the central path, and the affine scaling direction in interior point methods. The resulting solutions of the first two ODE systems are called generalized affine scaling trajectory and generalized central path, respectively. Under some mild conditions, the properties of the continuous trajectories, the optimality and convergence of the continuous trajectories are all obtained. Furthermore, we show that for the example of Gilbert et al. [Math. Program., { 103}, 63-94 (2005)], where the central path does not converge, our generalized central path converges to an optimal solution of the same example in the limit.. Then we analyze two primal dual continuous trajectories for convex programming. The two continuous trajectories are derived from the primal-dual path-following method and the primal-dual affine scaling method, respectively. Theoretical properties of the two interior point continuous trajectories are fully studied. The optimality and convergence of both interior point continuous trajectories are obtained for any interior feasible point under some mild conditions. In particular, with proper choice of some parameters, the convergence for both continuous trajectories does not require the strict complementarity or the analyticity of the objective function.. For convex semidefinite programming, four interior continuous trajectories defined by matrix differential equations are proposed and analyzed. Optimality and convergence of the continuous trajectories are also obtained under some mild conditions. We also propose a strategy to guarantee the optimality of the affine scaling algorithm for convex SDP.
6

Convex programming without constraint qualification : a study of Pareto optimality

Fraklin, Martin Gordon. January 1975 (has links)
No description available.
7

Solving discrete minimax problems with constraints

Turner, Bella Tobie January 1976 (has links)
No description available.
8

The generalized inverse dual for quadratically constrained quadratic programs

Randolph, William David, January 1974 (has links)
Thesis--University of Florida. / Description based on print version record. Typescript. Vita. Bibliography: leaves 107-111.
9

Convergence and approximation for primal-dual methods in large-scale optimization /

Wright, Stephen E., January 1990 (has links)
Thesis (Ph. D.)--University of Washington, 1990. / Vita. Includes bibliographical references (leaves [97]-100).
10

Biconvex programming and deterministic and stochastic location allocation problems

Selim, Shokri Zaki 12 1900 (has links)
No description available.

Page generated in 0.1523 seconds