High Performance Algorithms and Software for Nonlinear Optimization -

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Résumé :
PThe chapters included in this volume, which are authored by some of the most well-known researchers in nonlinear optimization, give an updated overview of the field from different and complementary standpoints: theoretical analysis, algorithmic developments, software evaluation, implementation issues, and applications./P PEMAudience:/EM This volume would be useful to researchers and professionals working in applied mathematics, advanced engineering, computer sciences, as well as graduate students. /P

Sommaire:
1. Quasi-Newton Algorithms for Large-Scale Nonlinear Least-Squares.- 2. The Extended Ritz Method in Stochastic Functional Optimizazion: An Example of Dynamic Routing in Traffic Networks.- 3. Efficient Serial and Parallel Implementation of the Cutting Angle Method.- 4. A Globalization Strategy for Interior Point Methods for Mixed Complementarity Problems.- 5. A Comparative Study of Large-Scale Nonlinear Optimization Algorithms.- 6. A Software System for PDE-Constrained Optimization Problems.- 7. A Truncated SQP Algorithm for Solving Nonconvex Equality Constrained Optimization Problems.- 8. Newton-Type Methods for the Approximate Solution of Nonlinear Programming Problems in Real-Time.- 9. Fruitful Uses of Smooth Exact Merit Functions in Constrained Optimization.- 10. New Perspective on the Theorems of Alternative.- 11. Planar-CG Methods and Matrix Tridiagonalization in Large Scale Unconstrained Optimization.- 12. Filter-type Algorithms for Solving Systems of Algebraic Equations and Inequalities.- 13. A New Algorithm for Solving Large Scale Molecular Distance Geometry Problems.- 14. PENNON A generalized Augmented Lagrangian Method for Semidefinite Programming.- 15. Understanding Asynchronous Parallel Pattern Search.- 16. Smoothing Techniques for the Solution of Finite and Semi-Infinite Min-Max-Min Problems.- 17. Exploiting Optimality Conditions in Accurate Static Circuit Tuning.- 18. Efficient Analysis on a Truncated Newton Method with Preconditioned Conjugate Gradient Technique for Optimization.