Superlinearly Convergent Exact Penalty Projected Structured Schemes for Constrained Nonlinear Least Squares, Ph.D. Dissertation Sharif University of Technology ; Mahdavi Amiri, Nezamoddin (Supervisor)
Abstract
We present two projected structured algorithms for solving nonlinearly constrained nonlinear least squares problems. The first algorithm makes use of a line search scheme and the second algorithm utilizes a combined trust region-line search scheme. These approaches are based on an adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method of Coleman and Conn for nonlinearly constrained optimization problems. The structured adaptation also makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected structured Hessians and appropriates the structuring scheme of Dennis, Martinez and Tapia. For robustness of the first algorithm, we...
Cataloging briefSuperlinearly Convergent Exact Penalty Projected Structured Schemes for Constrained Nonlinear Least Squares, Ph.D. Dissertation Sharif University of Technology ; Mahdavi Amiri, Nezamoddin (Supervisor)
Abstract
We present two projected structured algorithms for solving nonlinearly constrained nonlinear least squares problems. The first algorithm makes use of a line search scheme and the second algorithm utilizes a combined trust region-line search scheme. These approaches are based on an adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method of Coleman and Conn for nonlinearly constrained optimization problems. The structured adaptation also makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected structured Hessians and appropriates the structuring scheme of Dennis, Martinez and Tapia. For robustness of the first algorithm, we...
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