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Books Books 1 - 10 of about 45 related to Practical optimization.    

Sparse matrix methods in optimization

Philip E. Gill, Walter Murray, Michael A. Saunders, Margaret H. Wright - 1982 - 34 pages
Optimization algorithms typically require the solution of many systems of linear equations B sub Y sub = b sub. When large numbers of variables or constraints are present ...
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A projected Lagrangian algorithm for nonlinear minimax optimization

Walter Murray, Michael L. Overton - 1979 - 74 pages
The minimax problem is an unconstrained optimization problem whose objective functions is not differentiable everywhere, and hence cannot be solved efficiently by standard ...
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QP based methods for large scale nonlinearly constrained optimization

Philip E. Gill, Stanford University. Systems Optimization Laboratory, W. Murray, M. A. Saunders, M. H. Wright - Mathematical optimization - 1981 - 23 pages
Several methods for nonlinearly constrained optimization have been suggested in recent years that are based on solving a quadratic programming (QP) subproblem to determine the ...
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Projected Lagrangian methods based on the trajectories of penalty and ...

Walter Murray, Margaret H. Wright - 1978 - 71 pages
This report contains a complete derivation and description of two algorithms for nonlinearly constrained optimization which are based on properties of the solution trajectory ...
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Numerical Aspects of Trajectory Algorithms for Nonlinearly Constrained ...

Stanford University. Dept. of Operations Research. Systems Optimization Laboratory, Walter Murray, Margaret H. Wright - 1976 - 11 pages
This paper discusses two algorithms for nonlinearly constrained optimization. These algorithms -- the penalty and barrier trajectory algorithms -- are based on an examination ...
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