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Interior-Point Gradient Methods with Diagonal-Scalings for Simple-Bound Constrained Optimization
In this paper, we study diagonally scaled gradient methods for simple-bound constrained optimization in a framework almost identical to that for unconstrained optimization, except that iterates are kept within the interior ...
An Interior-Point Gradient Method for Large-Scale Totally Nonnegative Least Squares Problems
We study an interior-point gradient method for solving a class of so-called totally nonnegative least squares problems. At each iteration, the method decreases the residual norm along a diagonally scaled negative gradient ...
A Geometric Approach to Fluence Map Optimization in IMRT Cancer Treatment Planning
Intensity-modulated radiation therapy (IMRT) is a state-of-the-art technique for administering radiation to cancer patients. The goal of a treatment is to deliver a prescribed amount of radiation to the tumor, while limiting ...
A General Robust-Optimization Formulation for Nonlinear Programming
Most research in robust optimization has so far been focused on inequality-only, convex conic programming with simple linear models for uncertain parameters. Many practical optimization problems, however, are nonlinear and ...