Deterministic Global OptimizationSpringer Science & Business Media, 2000 - 739 lappuses This book provides a unified and insightful treatment of deterministic global optimization. It introduces theoretical and algorithmic advances that address the computation and characterization of global optima, determine valid lower and upper bounds on the global minima and maxima, and enclose all solutions of nonlinear constrained systems of equations. Among its special features, the book: Introduces the fundamentals of deterministic global optimization; Provides a thorough treatment of decomposition-based global optimization approaches for biconvex and bilinear problems; Covers global optimization methods for generalized geometric programming problems Presents in-depth global optimization algorithms for general twice continuously differentiable nonlinear problems; Provides a detailed treatment of global optimization methods for mixed-integer nonlinear problems; Develops global optimization approaches for the enclosure of all solutions of nonlinear constrained systems of equations; Includes many important applications from process design, synthesis, control, and operations, phase equilibrium, design under uncertainty, parameter estimation, azeotrope prediction, structure prediction in clusters and molecules, protein folding, and peptide docking. Audience: This book can be used as a textbook in graduate-level courses and as a desk reference for researchers in all branches of engineering and applied science, applied mathematics, industrial engineering, operations research, computer science, economics, computational chemistry and molecular biology. |
No grāmatas satura
1.–5. rezultāts no 46.
vii. lappuse
... Illustrative Applications of Global Optimization 3 4 1.4 Deterministic Global Optimization : Approaches and Classes of Problems 1.5 Complexity Analysis 1.6 Research Areas and Important Applications 18 19 23 1.7 Publications and ...
... Illustrative Applications of Global Optimization 3 4 1.4 Deterministic Global Optimization : Approaches and Classes of Problems 1.5 Complexity Analysis 1.6 Research Areas and Important Applications 18 19 23 1.7 Publications and ...
viii. lappuse
... Illustrative Example for the NRTL n - Butyl - Acetate - Water 7. THE GOP APPROACH : DISTRIBUTED IMPLEMENTATION 7.1 Critical Components of the Distributed GOP Approach 7.2 Large Scale Indefinite Quadratic Problems 7.3 Large Scale Pooling ...
... Illustrative Example for the NRTL n - Butyl - Acetate - Water 7. THE GOP APPROACH : DISTRIBUTED IMPLEMENTATION 7.1 Critical Components of the Distributed GOP Approach 7.2 Large Scale Indefinite Quadratic Problems 7.3 Large Scale Pooling ...
ix. lappuse
... Illustrative Example 334 334 340 342 355 12.6 Global Optimization Algorithm , aBB 12.7 Geometrical Interpretation of the aBB Approach 361 365 13.2 Implementation of the aBB 13. COMPUTATIONAL STUDIES OF THE ABB APPROACH 13.1 Algorithmic ...
... Illustrative Example 334 334 340 342 355 12.6 Global Optimization Algorithm , aBB 12.7 Geometrical Interpretation of the aBB Approach 361 365 13.2 Implementation of the aBB 13. COMPUTATIONAL STUDIES OF THE ABB APPROACH 13.1 Algorithmic ...
x. lappuse
... Illustrative Example 528 18.6 Mixed - Product Campaign Formulation 530 18.7 Computational Studies 18.8 Comparison to Alternative Underestimating Approaches 19. THE ABB APPROACH IN PARAMETER ESTIMATION 19.1 Introduction 533 538 543 543 ...
... Illustrative Example 528 18.6 Mixed - Product Campaign Formulation 530 18.7 Computational Studies 18.8 Comparison to Alternative Underestimating Approaches 19. THE ABB APPROACH IN PARAMETER ESTIMATION 19.1 Introduction 533 538 543 543 ...
1. lappuse
Atvainojiet, šīs lappuses saturs ir ierobežots..
Atvainojiet, šīs lappuses saturs ir ierobežots..
Saturs
II | 1 |
V | 3 |
VI | 4 |
VII | 18 |
VIII | 19 |
IX | 23 |
X | 25 |
XI | 27 |
LXXVIII | 382 |
LXXIX | 384 |
LXXX | 403 |
LXXXI | 409 |
LXXXII | 418 |
LXXXIII | 423 |
LXXXIV | 425 |
LXXXV | 426 |
XII | 32 |
XIII | 33 |
XIV | 35 |
XV | 42 |
XVI | 45 |
XVII | 57 |
XVIII | 58 |
XIX | 67 |
XX | 68 |
XXI | 70 |
XXII | 73 |
XXIII | 82 |
XXIV | 84 |
XXV | 87 |
XXVI | 90 |
XXVII | 95 |
XXVIII | 96 |
XXIX | 98 |
XXX | 105 |
XXXI | 114 |
XXXII | 126 |
XXXIII | 134 |
XXXIV | 141 |
XXXVII | 152 |
XXXVIII | 168 |
XXXIX | 173 |
XL | 175 |
XLI | 181 |
XLII | 187 |
XLIII | 193 |
XLIV | 198 |
XLV | 212 |
XLVI | 225 |
XLVII | 229 |
XLVIII | 234 |
XLIX | 243 |
L | 247 |
LI | 251 |
LII | 257 |
LIII | 261 |
LIV | 276 |
LV | 282 |
LVI | 283 |
LVII | 289 |
LVIII | 297 |
LIX | 309 |
LX | 311 |
LXI | 315 |
LXIII | 318 |
LXIV | 323 |
LXV | 324 |
LXVI | 326 |
LXVII | 329 |
LXVIII | 333 |
LXX | 334 |
LXXII | 340 |
LXXIII | 342 |
LXXIV | 355 |
LXXV | 361 |
LXXVI | 365 |
LXXVII | 377 |
LXXXVI | 431 |
LXXXVII | 432 |
LXXXVIII | 435 |
XCI | 438 |
XCII | 439 |
XCIII | 444 |
XCIV | 447 |
XCV | 451 |
XCVIII | 452 |
XCIX | 459 |
C | 466 |
CI | 471 |
CII | 481 |
CV | 483 |
CVI | 485 |
CVII | 488 |
CVIII | 490 |
CIX | 494 |
CX | 498 |
CXI | 507 |
CXII | 509 |
CXIII | 517 |
CXIV | 524 |
CXV | 528 |
CXVI | 530 |
CXVII | 533 |
CXVIII | 538 |
CXIX | 543 |
CXXII | 545 |
CXXIII | 548 |
CXXIV | 551 |
CXXV | 554 |
CXXVI | 571 |
CXXIX | 575 |
CXXX | 576 |
CXXXI | 579 |
CXXXII | 587 |
CXXXV | 588 |
CXXXVI | 590 |
CXXXVII | 591 |
CXXXVIII | 592 |
CXXXIX | 595 |
CXL | 598 |
CXLI | 617 |
CXLII | 618 |
CXLIV | 621 |
CXLV | 622 |
CXLVII | 624 |
CXLIX | 641 |
CL | 643 |
CLI | 646 |
CLII | 653 |
CLIII | 657 |
CLIV | 667 |
CLV | 668 |
CLVI | 670 |
CLVII | 672 |
CLVIII | 692 |
699 | |
Citi izdevumi - Skatīt visu
Deterministic Global Optimization: Theory, Methods and Applications Christodoulos A. Floudas Ierobežota priekšskatīšana - 2013 |
Deterministic Global Optimization: Theory, Methods and Applications Christodoulos A. Floudas Priekšskatījums nav pieejams - 2010 |
Bieži izmantoti vārdi un frāzes
aBB algorithm Adjiman atoms azeotropes bilinear terms binary variables bound updates bounding function branch and bound Chapter concave concave function connected variables convergence convex envelope convex functions convex lower bounding convex relaxation convex set convex underestimators corresponding defined dihedral angles eigenvalue equation feasible formulation fractional Gibbs free energy global minimum global optimization algorithm global optimization approach global solution GMIN-aBB GOP algorithm Hessian matrix integer interval Lagrange function linear lower bounding function lower bounding problem Maranas and Floudas maximum separation methods microclusters minimization MINLP node nonconvex terms nonlinear number of iterations objective function obtained optimal solution optimization problem parameters peptide potential energy primal problem properties quadratic qualifying constraints region relaxed dual problem relaxed dual subproblems shift matrix solvation solved Table Theorem upper bound variable bounds vector
Populāri fragmenti
710. lappuse - IA (1992) Crystal structures of two viral peptides in complex with murine MHC class I H-2Kb. Science 257, 919-927.
715. lappuse - JL Klepeis, IP Androulakis, MG lerapetritou, and CA Floudas. Predicting Solvated Peptide Conformations via Global Minimization of Energetic Atom to Atom Interactions.
706. lappuse - R. L DesJarlais, RP Sheridan, GL Seibel, JS Dixon, ID Kuntz, and R. Venkataraghavan, Using shape complementarity as an initial screen in designing ligands for a receptor binding site of known three-dimensional structure.
714. lappuse - RC Glen. Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J. Mol. Biol.
724. lappuse - Comp. Chem. 1993, 14, 349-352 (matching of point-by-point representation of surface for correlation with hydration energies in fast molecular dynamics calculations); Perrot, GB; Cheng, KD; Gibson, J.; Vila, KA; Palmer, A.; Nayeem, B.; Maigret; Scheraga, HA MSEED: A program for the rapid analytical determination of accessible surface areas and their derivatives, J.
727. lappuse - Mapped continuation methods for computing all solutions to general systems of nonlinear equations.
731. lappuse - V. Visweswaran and CA Floudas. Computational results for an efficient implementation of the GOP algorithm and its variants. In IE Grossmann.
Atsauces uz šo grāmatu
Frontiers in Global Optimization Christodoulos A. Floudas,Panos M. Pardalos Ierobežota priekšskatīšana - 2004 |