Advances in Convex Analysis and Global Optimization: Honoring the Memory of C. Caratheodory (1873–1950)Nicolas Hadjisavvas, Panos M. Pardalos Springer Science & Business Media, 1 thg 12, 2013 - 597 trang There has been much recent progress in global optimization algo rithms for nonconvex continuous and discrete problems from both a theoretical and a practical perspective. Convex analysis plays a fun damental role in the analysis and development of global optimization algorithms. This is due essentially to the fact that virtually all noncon vex optimization problems can be described using differences of convex functions and differences of convex sets. A conference on Convex Analysis and Global Optimization was held during June 5 -9, 2000 at Pythagorion, Samos, Greece. The conference was honoring the memory of C. Caratheodory (1873-1950) and was en dorsed by the Mathematical Programming Society (MPS) and by the Society for Industrial and Applied Mathematics (SIAM) Activity Group in Optimization. The conference was sponsored by the European Union (through the EPEAEK program), the Department of Mathematics of the Aegean University and the Center for Applied Optimization of the University of Florida, by the General Secretariat of Research and Tech nology of Greece, by the Ministry of Education of Greece, and several local Greek government agencies and companies. This volume contains a selective collection of refereed papers based on invited and contribut ing talks presented at this conference. The two themes of convexity and global optimization pervade this book. The conference provided a forum for researchers working on different aspects of convexity and global opti mization to present their recent discoveries, and to interact with people working on complementary aspects of mathematical programming. |
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Deterministic Global Optimization for Protein Structure | 31 |
Some Remarks on Minimum Principles 75 | 74 |
Transversal Hypergraphs and Families of Polyhedral Cones | 105 |
SDP Relaxations in Combinatorial Optimization from a | 119 |
Convex Analysis in the Calculus of Variations | 135 |
Global Minimization and Parameter Estimation in Compu | 152 |
Approximate Analytic Center Quadratic Cut Method | 345 |
Generating Convex Functions | 367 |
A Pivotingbased Heuristic for the Maximum Clique Prob | 383 |
An Analytic Center Self Concordant Cut Method for | 395 |
Strengthened Semidefinite Programming Relaxations | 409 |
Supervised Training Using Global Search Methods | 429 |
Learning | 437 |
Improving the Particle Swarm Optimizer by Function | 445 |
Lagrangian Quadratic Bounds in Polynomial Nonconvex | 181 |
Generalized Duality in Variational Analysis | 205 |
H Tuy A M Bagirov and A M Rubinov | 221 |
Algorithms and Merit Functions for the Principal Eigen | 235 |
Modified Versions of the Cutting Angle Method | 245 |
Theoretical and Computational Results for a Linear Bilevel | 269 |
The Lagrangian Search Method | 282 |
16 | 295 |
Restoration of Signal 1D and 2D | 303 |
New Positive Semidefinite Relaxations for Nonconvex | 318 |
Interval Analysis Applied to Global Minimization | 333 |
Some Convergence Properties of the Steepest Descent | 458 |
InteriorPoint Algorithm for Dantzig and Wolfe Decompo | 473 |
Stochastic Perturbation Methods for Affine Restrictions 487 | 486 |
Directed | 501 |
A Perturbed Auxiliary Problem Method for Paramonotone | 515 |
A Note on Random Variational Inequalities and Simple Ran | 530 |
A Comparison Principle and the Lipschitz Continuity | 545 |
Tunneling | 552 |
Convexity and Monotonicity in Global Optimization | 569 |
Ấn bản in khác - Xem tất cả
Advances in Convex Analysis and Global Optimization: Honoring the Memory of ... Constantin Carathéodory Xem trước bị giới hạn - 2001 |
Advances in Convex Analysis and Global Optimization: Honoring the Memory of ... Nicolas Hadjisavvas,Panos M. Pardalos Không có bản xem trước - 2011 |
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Advances in Convex algorithm Analysis and Global analytic center applied approach approximation branch and bound calculated calculus of variations CGU method combinatorial computational condition cone consider constraints convergence Convex Analysis convex function convex set corresponding defined denote differentiable dihedral angle dual duality eigenvalue energy conformation energy function equation equivalent feasible finite Floudas formulation free energy given global minimum global optimization gradient graph hypergraph iteration Lagrange Lagrangian Lemma linear Lipschitz lower bound Mathematics matrix max-cut maximal minimization molecules monotone nonconvex objective function obtained optimal value optimization problem P.M. Pardalos eds parameters polynomial polytope potential Proof Proposition protein folding quadratic relaxation semidefinite semidefinite programming sequence simulated annealing solution solving space Step structure subset Theorem tion upper bound variables variational inequality vector weight