Nonlinear programming:
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Belmont, Mass.
Athena Scientific
2003
|
| Ausgabe: | 2. ed., 2. print. |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013043262&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XIV, 786 S. Ill., graph. Darst. |
| ISBN: | 1886529000 |
Internformat
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| 100 | 1 | |a Bertsekas, Dimitri P. |d 1942- |e Verfasser |0 (DE-588)171165519 |4 aut | |
| 245 | 1 | 0 | |a Nonlinear programming |c Dimitri P. Bertsekas |
| 250 | |a 2. ed., 2. print. | ||
| 264 | 1 | |a Belmont, Mass. |b Athena Scientific |c 2003 | |
| 300 | |a XIV, 786 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 0 | 7 | |a Nichtlineare Optimierung |0 (DE-588)4128192-5 |2 gnd |9 rswk-swf |
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-013043262 | |
Datensatz im Suchindex
| DE-BY-TUM_call_number | 0041 MAT 916f 2007 A 4732(2,2) 0102 MAT 916 2001 A 7537(2,2) |
|---|---|
| DE-BY-TUM_katkey | 1595075 |
| DE-BY-TUM_location | LSB 01 |
| DE-BY-TUM_media_number | 040006571044 040071406132 |
| _version_ | 1821934237680402432 |
| adam_text | Contents
1. Unconstrained Optimization p. 1
1.1. Optimality Conditions p. 4
1.1.1. Variational Ideas p. 4
1.1.2. Main Optimality Conditions p. 13
1.2. Gradient Methods Convergence p. 22
1.2.1. Descent Directions and Stepsize Rules p. 22
1.2.2. Convergence Results p. 43
1.3. Gradient Methods Rate of Convergence p. 61
1.3.1. The Local Analysis Approach p. 63
1.3.2. The Role of the Condition Number p. 65
1.3.3. Convergence Rate Results p. 75
1.4. Newton s Method and Variations p. 88
1.5. Least Squares Problems p. 102
1.5.1. The Gauss Newton Method p. 107
1.5.2. Incremental Gradient Methods* p. 109
1.5.3. Incremental Forms of the Gauss Newton Method* . . . . p. 119
1.6. Conjugate Direction Methods p. 130
1.7. Quasi Newton Methods p. 148
1.8. Nonderivative Methods p. 159
1.8.1. Coordinate Descent p. 160
1.8.2. Direct Search Methods p. 162
1.9. Discrete Time Optimal Control Problems* p. 166
1.10. Some Practical Guidelines p. 183
1.11. Notes and Sources p. 187
2. Optimization Over a Convex Set p. 191
2.1. Constrained Optimization Problems p. 192
2.1.1. Necessary and Sufficient Conditions for Optimality .... p. 193
2.1.2. Existence of Optimal Solutions* p. 204
2.2. Feasible Directions and the Conditional Gradient Method . . p. 214
2.2.1. Descent Directions and Stepsize Rules p. 215
2.2.2. The Conditional Gradient Method p. 220
v
vi Contents
2.3. Gradient Projection Methods p. 228
2.3.1. Feasible Directions and Stepsize Rules Based on Projection p. 228
2.3.2. Convergence Analysis* p. 239
2.4. Two Metric Projection Methods p. 249
2.5. Manifold Suboptimization Methods p. 255
2.6. AfEne Scaling for Linear Programming p. 264
2.7. Block Coordinate Descent Methods* p. 272
2.8. Notes and Sources p. 277
3. Lagrange Multiplier Theory p. 281
3.1. Necessary Conditions for Equality Constraints p. 283
3.1.1. The Penalty Approach p. 287
3.1.2. The Elimination Approach p. 289
3.1.3. The Lagrangian Function p. 293
3.2. Sufficient Conditions and Sensitivity Analysis p. 302
3.2.1. The Augmented Lagrangian Approach p. 303
3.2.2. The Feasible Direction Approach p. 305
3.2.3. Sensitivity* p. 307
3.3. Inequality Constraints p. 313
3.3.1. Karush Kuhn Tucker Optimality Conditions p. 315
3.3.2. Conversion to the Equality Case* p. 318
3.3.3. Second Order Sufficiency Conditions and Sensitivity* ... p. 320
3.3.4. Sufficiency Conditions and Lagrangian Minimization* . . p. 321
3.3.5. Fritz John Optimality Conditions* p. 323
3.3.6. Refinements* p. 338
3.4. Linear Constraints and Duality* p. 365
3.4.1. Convex Cost Functions and Linear Constraints p. 365
3.4.2. Duality Theory: A Simple Form for Linear Constraints . . p. 368
3.5. Notes and Sources p. 377
4. Lagrange Multiplier Algorithms p. 379
4.1. Barrier and Interior Point Methods p. 380
4.1.1. Linear Programming and the Logarithmic Barrier* .... p. 383
4.2. Penalty and Augmented Lagrangian Methods p. 397
4.2.1. The Quadratic Penalty Function Method p. 399
4.2.2. Multiplier Methods Main Ideas p. 408
4.2.3. Convergence Analysis of Multiplier Methods* p. 417
4.2.4. Duality and Second Order Multiplier Methods* p. 420
4.2.5. The Exponential Method of Multipliers* p. 423
4.3. Exact Penalties Sequential Quadratic Programming* ... p. 431
4.3.1. Nondifferentiable Exact Penalty Functions p. 432
4.3.2. Differentiable Exact Penalty Functions p. 448
4.4. Lagrangian and Primal Dual Interior Point Methods* .... p. 455
4.4.1. First Order Methods p. 455
Contents vii
4.4.2. Newton Like Methods for Equality Constraints p. 459
4.4.3. Global Convergence p. 469
4.4.4. Primal Dual Interior Point Methods p. 472
4.4.5. Comparison of Various Methods p. 480
4.5. Notes and Sources p. 482
5. Duality and Convex Programming p. 485
5.1. The Dual Problem p. 487
5.1.1. Lagrange Multipliers p. 488
5.1.2. The Weak Duality Theorem p. 493
5.1.3. Characterization of Primal and Dual Optimal Solutions . . p. 498
5.1.4. The Case of an Infeasible or Unbounded Primal Problem . p. 500
5.1.5. Treatment of Equality Constraints p. 500
5.1.6. Separable Problems and Their Geometry p. 502
5.1.7. Additional Issues About Duality p. 506
5.2. Convex Cost Linear Constraints* p. 514
5.3. Convex Cost Convex Constraints p. 520
5.4. Conjugate Functions and Fenchel Duality* p. 529
5.4.1. Monotropic Programming Duality p. 534
5.4.2. Network Optimization p. 537
5.4.3. Games and the Minimax Theorem p. 540
5.4.4. The Primal Function p. 542
5.4.5. A Dual View of Penalty Methods p. 544
5.4.6. The Proximal and Entropy Minimization Algorithms ... p. 550
5.5. Discrete Optimization and Duality p. 568
5.5.1. Examples of Discrete Optimization Problems p. 569
5.5.2. Branch and Bound p. 577
5.5.3. Lagrangian Relaxation p. 586
5.6. Notes and Sources p. 598
6. Dual Methods p. 601
6.1. Dual Derivatives and Subgradients* p. 604
6.2. Dual Ascent Methods for Differentiablo Dual Problems* ... p. 610
6.2.1. Coordinate Ascent for Quadratic Programming p. 610
6.2.2. Decomposition and Primal Strict Convexity p. 613
6.2.3. Partitioning and Dual Strict Concavity p. 614
6.3. Nondifferentiable Optimization Methods* p. 619
6.3.1. Subgradient Methods p. 620
6.3.2. Approximate and Incremental Subgradient Methods ... p. 625
6.3.3. Cutting Plane Methods p. 629
6.3.4. Ascent and Approximate Ascent Methods p. 636
6.4. Decomposition Methods* p. 650
6.4.1. Lagrangian Relaxation of the Coupling Constraints . . . . p. 651
6.4.2. Decomposition by Right Hand Side Allocation p. 655
viii Contents
6.5. Notes and Sources p. 657
Appendix A: Mathematical Background p. 659
A.I. Vectors and Matrices p. 660
A.2. Norms, Sequences, Limits, and Continuity p. 663
A.3. Square Matrices and Eigenvalues p. 671
A.4. Symmetric and Positive Definite Matrices p. 674
A.5. Derivatives p. 679
A.6. Contraction Mappings p. 684
Appendix B: Convex Analysis p. 687
B.I. Convex Sets and Functions p. 687
B.2. Separating Hyperplanes p. 708
B.3. Cones and Polyhedral Convexity p. 713
B.4. Extreme Points p. 721
B.5. Differentiability Issues p. 726
Appendix C: Line Search Methods p. 741
C.I. Cubic Interpolation p. 741
C.2. Quadratic Interpolation p. 742
C.3. The Golden Section Method p. 744
Appendix D: Implementation of Newton s Method ... p. 747
D.I. Cholesky Factorization p. 747
D.2. Application to a Modified Newton Method p. 749
References p. 753
Index p. 783
|
| any_adam_object | 1 |
| author | Bertsekas, Dimitri P. 1942- |
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| callnumber-subject | T - General Technology |
| classification_rvk | QH 421 SK 870 |
| classification_tum | MAT 916f |
| ctrlnum | (OCoLC)255890653 (DE-599)BVBBV019716008 |
| dewey-full | 519.7/6 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.7/6 |
| dewey-search | 519.7/6 |
| dewey-sort | 3519.7 16 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 2. ed., 2. print. |
| format | Book |
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| id | DE-604.BV019716008 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T12:04:21Z |
| institution | BVB |
| isbn | 1886529000 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-013043262 |
| oclc_num | 255890653 |
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| owner_facet | DE-20 DE-384 DE-703 DE-188 DE-91G DE-BY-TUM |
| physical | XIV, 786 S. Ill., graph. Darst. |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | Athena Scientific |
| record_format | marc |
| spellingShingle | Bertsekas, Dimitri P. 1942- Nonlinear programming Nichtlineare Optimierung (DE-588)4128192-5 gnd |
| subject_GND | (DE-588)4128192-5 |
| title | Nonlinear programming |
| title_auth | Nonlinear programming |
| title_exact_search | Nonlinear programming |
| title_full | Nonlinear programming Dimitri P. Bertsekas |
| title_fullStr | Nonlinear programming Dimitri P. Bertsekas |
| title_full_unstemmed | Nonlinear programming Dimitri P. Bertsekas |
| title_short | Nonlinear programming |
| title_sort | nonlinear programming |
| topic | Nichtlineare Optimierung (DE-588)4128192-5 gnd |
| topic_facet | Nichtlineare Optimierung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013043262&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT bertsekasdimitrip nonlinearprogramming |
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Handapparate (nicht verfügbar)
| Signatur: |
0041 MAT 916f 2007 A 4732(2,2) Lageplan |
|---|---|
| Exemplar 1 | Dauerhaft ausgeliehen Ausgeliehen – Rückgabe bis: 31.12.9999 |
Teilbibliothek Mathematik & Informatik
| Signatur: |
0102 MAT 916 2001 A 7537(2,2) Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |