Title | Advances in Convex Analysis and Global Optimization [electronic resource] : Honoring the Memory of C. Caratheodory (1873-1950) / edited by Nicolas Hadjisavvas, Panos M. Pardalos |
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Imprint | Boston, MA : Springer US, 2001 |
Connect to | http://dx.doi.org/10.1007/978-1-4613-0279-7 |
Descript | XXIV, 597 p. online resource |
1. Inner Approximation of State-constrained Optimal Control Problems -- 2. Nonsmooth Problems in Mathematical Diagnostics -- 3. Deterministic Global Optimization for Protein Structure Prediction -- 4. Some Remarks on Minimum Principles -- 5. Transversal Hypergraphs and Families of Polyhedral Cones -- 6. SDP Relaxations in Combinatorial Optimization from a Lagrangian Viewpoint -- 7. Convex Analysis in the Calculus of Variations -- 8. Global Minimization and Parameter Estimation in Computational Biology -- 9. Lagrangian Quadratic Bounds in Polynomial Nonconvex and Boolean Models with Superfluous Constraints -- 10. Generalized Duality in Variational Analysis -- 11. Clustering via D. C. Optimization -- 12. Algorithms and Merit Functions for the Principal Eigen-value -- 13. Modified Versions of the Cutting Angle Method -- 14. Theoretical and Computational Results for a Linear Bilevel Problem -- 15. The Lagrangian Search Method -- 16. An ?โ{128}{148}maximum Principle for Generalized Control Systems -- 17. D.C. Optimization Approaches via Markov Models for Restoration of Signal (1-D) and (2-D) -- 18. New Positive Semidefinite Relaxations for Nonconvex Quadratic Programs -- 19. Interval Analysis Applied to Global Minimization -- 20. Approximate Analytic Center Quadratic Cut Method for Strongly Monotone Variational Inequalities -- 21. Generating Convex Functions -- 22. The Method of Moments for Nonconvex Variational Problems -- 23. A Pivoting-based Heuristic for the Maximum Clique Problem -- 24. An Analytic Center Self Concordant Cut Method for the Convex Feasibility Problem -- 25. Strengthened Semidefinite Programming Relaxations for the Max-Cut Problem -- 26. Supervised Training Using Global Search Methods -- 27. Learning Rate Adaptation in Stochastic Gradient Descent -- 28. Improving the Particle Swarm Optimizer by Function โ{128}{156}Stretchingโ{128}{157} -- 29. Some Convergence Properties of the Steepest Descent Algorithm Revealed by Renormalisation -- 30. Interiorโ{128}{148}Point Algorithm for Dantzig and Wolfe Decomposition Principle -- 31. Stochastic Perturbation Methods for Affine Restrictions -- 32. Directed Derivatives of Convex Compact-Valued Mappings -- 33. A Perturbed Auxiliary Problem Method for Paramonotone Multivalued Mappings -- 34. A Note on Random Variational Inequalities and Simple Random Unilateral Boundary Value Problems -- 35. A Comparison Principle and the Lipschitz Continuity for Minimizers -- 36. Tunneling and Genetic Algorithms for Global Optimization -- 37. Convexity and Monotonicity in Global Optimization