Centering, Trust Region, Reflective Techniques for Nonlinear Minimization Subject to Bounds
Bound-constrained nonlinear minimization problems occur frequently in practice. Most existing methods belong to an active set type which can be slow for large scale problems. Recently, we proposed a new approach [7,6,8] which generates iterates within the strictly feasible region. The method in  is a trust region type and, unlike the existing trust region method for bound-constrained problems, the conditions for its strong convergence properties are consistent with algorithm implementation. A reflective technique can be included in the method. In this paper, we motivate techniques which are important for our new approach. Numerical experience on some medium size problems is included.
computer science; technical report
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