Now showing items 61-67 of 67
Variationally Constrained Numerical Solution of Electrical Impedance Tomography
We propose a novel, variational inversion methodology for the electrical impedance tomography problem, where we seek electrical conductivity σ inside a bounded, simply connected domain Ω, given simultaneous measurements ...
Computational Experience with Lenstra's Algorithm
Integer programming is an important mathematical approach for many decision-making problems. In this field, a major theoretical breakthrough came in 1983 when H. W. Lenstra, Jr. proposed a polynomial-time algorithm for a ...
A Successive Linear Programming Approach to IMRT Optimization Problem
We propose to solve the IMRT optimization problem through a successive linear programming approach. Taking advantage of the sensitivity information in linear programming and the re-optimization ability of simplex methods, ...
Accelerating Convergence by Augmented Rayleigh-Ritz Projections For Large-Scale Eigenpair Computation
Iterative algorithms for large-scale eigenpair computation are mostly based subspace projections consisting of two main steps: a subspace update (SU) step that generates bases for approximate eigenspaces, followed by a ...
An Optimal Basis Identification Technique for Interior-Point Linear Programming Algorithms
This work concerns a method for identifying an optimal basis for linear programming problems in the setting of interior point methods. To each iterate x^k generated by a primal interior point algorithm, say, we associate ...
On the Convergence of Interior-Point Methods to the Center of the Solution Set in Linear Programming
The notion of the central path plays an important role in the convergence analysis of interior-point methods. Many interior-point algorithms have been developed based on the principle of following the central path, either ...