Spelling suggestions: "subject:"1inear programming"" "subject:"alinear programming""
31 
An investigation of an exterior point method for linear programmingPudwill, Rodger A. 12 1900 (has links)
No description available.

32 
The development of mathematical models to describe seat allocation in stadiaHughey, Walter Lee 05 1900 (has links)
No description available.

33 
Affine scaling algorithms for linear programs and linearly constrained convex and concave programsWang, Yanhui 05 1900 (has links)
No description available.

34 
An algorithm for maximal flow with gains in a special networkJezior, Anthony Michael 12 1900 (has links)
No description available.

35 
Some properties of the affine scaling algorithmCastillo, Ileana 05 1900 (has links)
No description available.

36 
Toeplitz matrices and interior point methods for linear programmingCastillo, Ileana 05 1900 (has links)
No description available.

37 
2lattice polyhedraChang, ShiowYun 08 1900 (has links)
No description available.

38 
New algorithmic approaches for semidefinite programming with applications to combinatorial optimizationBurer, Samuel A. 08 1900 (has links)
No description available.

39 
The analytic center cutting plane method with semidefinite cuts /Oskoorouchi, Mohammad R. January 2002 (has links)
We propose an analytic center cutting plane algorithm for semidefinite programming (SDP). Reformulation of the dual problem of SDP into an eigenvalue optimization, when the trace of any feasible primal matrix is a positive constant, is well known. We transform the eigenvalue optimization problem into a convex feasibility problem. The problem of interest seeks a feasible point in a bounded convex set, which contains a full dimensional ball with &egr;(<1) radius and is contained in a compact convex set described by matrix inequalities, known as the set of localization. At each iteration, an approximate analytic center of the set of localization is computed. If this point is not in the solution set, an oracle is called to return a pdimensional semidefinite cut. The set of localization then, is updated by adding the semidefinite cut through the center. We prove that the analytic center is recovered after adding a pdimensional semidefinite cut in O(plog(p + 1)) damped Newton's iteration and that the ACCPM with semidefinite cuts is a fully polynomial approximation scheme. We report the numerical result of our algorithm when applied to the semidefinite relaxation of the MaxCut problem.

40 
A linear programming model for the analysis of traffic in a highway networkHeanue, Kevin Edward 12 1900 (has links)
No description available.

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