Advances in Convex Analysis and Global Optimization: Honoring the Memory of C. Caratheodory (1873–1950): Nonconvex Optimization and Its Applications, cartea 54
Editat de Nicolas Hadjisavvas, Panos M. Pardalosen Limba Engleză Paperback – 17 sep 2011
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Springer Us – 30 iun 2001 | 966.27 lei 6-8 săpt. |
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Specificații
ISBN-13: 9781461379751
ISBN-10: 146137975X
Pagini: 624
Ilustrații: XXIV, 597 p.
Dimensiuni: 160 x 240 x 33 mm
Greutate: 0.86 kg
Ediția:2001
Editura: Springer Us
Colecția Springer
Seria Nonconvex Optimization and Its Applications
Locul publicării:New York, NY, United States
ISBN-10: 146137975X
Pagini: 624
Ilustrații: XXIV, 597 p.
Dimensiuni: 160 x 240 x 33 mm
Greutate: 0.86 kg
Ediția:2001
Editura: Springer Us
Colecția Springer
Seria Nonconvex Optimization and Its Applications
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
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 ?—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 SwarmOptimizer by Function “Stretching”.- 29. Some Convergence Properties of the Steepest Descent Algorithm Revealed by Renormalisation.- 30. Interior—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.