Summary
The global convergence properties of a penalty-barrier method for solving equality and/or inequality constrained nonlinear optimization problems are considered. The presented algorithm is a composite of augmented Lagrangian, modified log-barrier, and classical log-barrier methods. Under common conditions, global convergence of a sequence of iterates to a first-order stationary point for the constrained problem is established. The iterates are approximate minima of a sequence of unconstrained penalty-barrier functions. Extensive computational tests suggest that the presented penalty-barrier algorithm is a robust and efficient method for solving general nonlinear optimization problems.
Keywords
- Global Convergence
- Nonlinear Program
- Nonlinear Optimization Problem
- Simple Bound
- Global Convergence Property
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© 1995 Springer-Verlag Berlin Heidelberg
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Breitfeld, M.G., Shanno, D.F. (1995). A Globally Convergent Penalty-Barrier Algorithm for Nonlinear Programming. In: Derigs, U., Bachem, A., Drexl, A. (eds) Operations Research Proceedings 1994. Operations Research Proceedings, vol 1994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79459-9_5
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DOI: https://doi.org/10.1007/978-3-642-79459-9_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-58793-4
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