Dual techniques for constrained optimization |
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Authors: | W W Hager |
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Institution: | (1) Department of Mathematics, Pennsylvania State University, University Park, Pennsylvania |
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Abstract: | Algorithms to solve constrained optimization problems are derived. These schemes combine an unconstrained minimization scheme like the conjugate gradient method, an augmented Lagrangian, and multiplier updates to obtain global quadratic convergence. Since an augmented Lagrangian can be ill conditioned, a preconditioning strategy is developed to eliminate the instabilities associated with the penalty term. A criterion for deciding when to increase the penalty is presented.This work was supported by the National Science Foundation, Grant Nos. MCS-81-01892, DMS-84-01758, and DMS-85-20926, and by the Air Force Office of Scientific Research, Grant No. AFOSR-ISSA-860091. |
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Keywords: | Constrained optimization duality augmented Lagrangians multiplier methods preconditioning null space methods |
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