Interior point methods for linear optimization:
Gespeichert in:
Hauptverfasser: | , , |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
New York
Springer
2006
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Ausgabe: | 2. ed. |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | 1. Aufl. u.d.T.: Roos, Cornelis: Theory and algorithms for linear optimization |
Beschreibung: | XXIV, 497 S. graph. Darst. |
ISBN: | 0387263780 |
Internformat
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245 | 1 | 0 | |a Interior point methods for linear optimization |c by Cornelis Roos ; Tamás Terlaky ; Jean-Philippe Vial |
250 | |a 2. ed. | ||
264 | 1 | |a New York |b Springer |c 2006 | |
300 | |a XXIV, 497 S. |b graph. Darst. | ||
336 | |b txt |2 rdacontent | ||
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500 | |a 1. Aufl. u.d.T.: Roos, Cornelis: Theory and algorithms for linear optimization | ||
650 | 4 | |a Algorithmes | |
650 | 7 | |a Innere-Punkte-Methode - Konvexe Optimierung |2 swd | |
650 | 7 | |a Innere-Punkte-Methode - Lineare Optimierung |2 swd | |
650 | 7 | |a Konvexe Optimierung - Innere-Punkte-Methode |2 swd | |
650 | 7 | |a Lineare Optimierung - Innere-Punkte-Methode |2 swd | |
650 | 4 | |a Optimisation mathématique | |
650 | 4 | |a Points intérieurs, Méthodes de | |
650 | 7 | |a Programação linear |2 larpcal | |
650 | 7 | |a Programação matemática |2 larpcal | |
650 | 4 | |a Programmation linéaire | |
650 | 4 | |a Algorithms | |
650 | 4 | |a Interior-point methods | |
650 | 4 | |a Linear programming | |
650 | 4 | |a Mathematical optimization | |
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700 | 1 | |a Terlaky, Tamás |e Verfasser |4 aut | |
700 | 1 | |a Vial, Jean-Philippe |e Verfasser |4 aut | |
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Datensatz im Suchindex
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adam_text | INTERIOR POINT METHODS FOR LINEAR OPTIMIZATION SECOND EDITION BY
CORNELIS ROOS DELFT UNIVERSITY OF TECHNOLOGY, THE NETHERLANDS TAMAES
TERLAKY MCMASTER UNIVERSITY, ONTARIO, CANADA JEAN-PHILIPPE VIAL
UNIVERSITY OF GENEVA, SWITZERLAND SPRINGER CONTENTS LIST OF FIGURES XV
LIST OF TABLES XVII PREFACE XIX ACKNOWLEDGEMENTS XXIII 1 INTRODUCTION 1
1.1 SUBJECT OF THE BOOK 1 1.2 MORE DETAILED DESCRIPTION OF THE CONTENTS
2 1.3 WHAT IS NEW IN THIS BOOK? 5 1.4 REQUIRED KNOWLEDGE AND SKILLS 6
1.5 HOW TO USE THE BOOK FOR COURSES 6 1.6 FOOTNOTES AND EXERCISES 8 1.7
PRELIMINARIES 8 1.7.1 POSITIVE DEFINITE MATRICES 8 1.7.2 NORMS OF
VECTORS AND MATRICES 8 1.7.3 HADAMARD INEQUALITY FOR THE DETERMINANT 11
1.7.4 ORDER ESTIMATES 11 1.7.5 NOTATIONAL CONVENTIONS 11 I INTRODUCTION:
THEORY AND COMPLEXITY 13 2 DUALITY THEORY FOR LINEAR OPTIMIZATION 15 2.1
INTRODUCTION 15 2.2 THE CANONICAL LO-PROBLEM AND ITS DUAL 18 2.3
REDUCTION TO INEQUALITY SYSTEM 19 2.4 INTERIOR-POINT CONDITION 20 2.5
EMBEDDING INTO A SELF-DUAL LO-PROBLEM 22 2.6 THE CLASSES B AND N 24 2.7
THE CENTRAL PATH 27 2.7.1 DEFINITION OF THE CENTRAL PATH 27 2.7.2
EXISTENCE OF THE CENTRAL PATH 29 2.8 EXISTENCE OF A STRICTLY
COMPLEMENTARY SOLUTION 35 2.9 STRONG DUALITY THEOREM 38 VIII CONTENTS
2.10 THE DUAL PROBLEM OF AN ARBITRARY LO PROBLEM 40 2.11 CONVERGENCE OF
THE CENTRAL PATH 43 3 A POLYNOMIAL ALGORITHM FOR THE SELF-DUAL MODEL 47
3.1 INTRODUCTION 47 3.2 FINDING AN E-SOLUTION 48 3.2.1 NEWTON-STEP
ALGORITHM 50 3.2.2 COMPLEXITY ANALYSIS 50 3.3 POLYNOMIAL COMPLEXITY
RESULT 53 3.3.1 INTRODUCTION 53 3.3.2 CONDITION NUMBER 54 3.3.3 LARGE
AND SMALL VARIABLES 57 3.3.4 FINDING THE OPTIMAL PARTITION 58 3.3.5 A
ROUNDING PROCEDURE FOR INTERIOR-POINT SOLUTIONS 62 3.3.6 FINDING A
STRICTLY COMPLEMENTARY SOLUTION 65 3.4 CONCLUDING REMARKS 70 4 SOLVING
THE CANONICAL PROBLEM 71 4.1 INTRODUCTION 71 4.2 THE CASE WHERE STRICTLY
FEASIBLE SOLUTIONS ARE KNOWN 72 4.2.1 ADAPTED SELF-DUAL EMBEDDING 73
4.2.2 CENTRAL PATHS OF (P) AND (D) 74 4.2.3 APPROXIMATE SOLUTIONS OF (P)
AND (D) 75 4.3 THE GENERAL CASE 78 4.3.1 INTRODUCTION 78 4.3.2
ALTERNATIVE EMBEDDING FOR THE GENERAL CASE 78 4.3.3 THE CENTRAL PATH OF
(SP 2 ) 80 4.3.4 APPROXIMATE SOLUTIONS OF (P) AND (D) 82 II THE
LOGARITHMIC BARRIER APPROACH 85 5 PRELIMINARIES 87 5.1 INTRODUCTION 87
5.2 DUALITY RESULTS FOR THE STANDARD LO PROBLEM 88 5.3 THE PRIMAL
LOGARITHMIC BARRIER FUNCTION 90 5.4 EXISTENCE OF A MINIMIZER 90 5.5 THE
INTERIOR-POINT CONDITION 91 5.6 THE CENTRAL PATH 95 5.7 EQUIVALENT
FORMULATIONS OF THE INTERIOR-POINT CONDITION 99 5.8 SYMMETRIE
FORMULATION 103 5.9 DUAL LOGARITHMIC BARRIER FUNCTION 105 6 THE DUAL
LOGARITHMIC BARRIER METHOD 107 6.1 A CONCEPTUAL METHOD 107 6.2 USING
APPROXIMATE CENTERS 109 6.3 DEFINITION OF THE NEWTON STEP 110 CONTENTS
IX 6.4 PROPERTIES OF THE NEWTON STEP 113 6.5 PROXIMITY AND LOCAL
QUADRATIC CONVERGENCE 114 6.6 THE DUALITY GAP CLOSE TO THE CENTRAL PATH
119 6.7 DUAL LOGARITHMIC BARRIER ALGORITHM WITH FUELL NEWTON STEPS 120
6.7.1 CONVERGENCE ANALYSIS 121 6.7.2 ILLUSTRATION OF THE ALGORITHM WITH
FUELL NEWTON STEPS 122 6.8 A VERSION OF THE ALGORITHM WITH ADAPTIVE
UPDATES 123 6.8.1 AN ADAPTIVE-UPDATE VARIANT 125 6.8.2 THE
AFFINE-SCALING DIRECTION AND THE CENTERING DIRECTION 127 6.8.3
CALCULATION OF THE ADAPTIVE UPDATE 127 6.8.4 ILLUSTRATION OF THE USE OF
ADAPTIVE UPDATES 129 6.9 A VERSION OF THE ALGORITHM WITH LARGE UPDATES
130 6.9.1 ESTIMATES OF BARRIER FUNCTION VALUES 132 6.9.2 ESTIMATES OF
OBJECTIVE VALUES 135 6.9.3 EFFECT OF LARGE UPDATE ON BARRIER FUNCTION
VALUE 138 6.9.4 DECREASE OF THE BARRIER FUNCTION VALUE 140 6.9.5 NUMBER
OF INNER ITERATIONS 142 6.9.6 TOTAL NUMBER OF ITERATIONS 143 6.9.7
ILLUSTRATION OF THE ALGORITHM WITH LARGE UPDATES 144 7 THE PRIMAL-DUAL
LOGARITHMIC BARRIER METHOD 149 7.1 INTRODUCTION 149 7.2 DEFINITION OF
THE NEWTON STEP 150 7.3 PROPERTIES OF THE NEWTON STEP 152 7.4 PROXIMITY
AND LOCAL QUADRATIC CONVERGENCE 154 7.4.1 A SHARPER LOCAL QUADRATIC
CONVERGENCE RESULT 159 7.5 PRIMAL-DUAL LOGARITHMIC BARRIER ALGORITHM
WITH FUELL NEWTON STEPS . . . 160 7.5.1 CONVERGENCE ANALYSIS 161 7.5.2
ILLUSTRATION OF THE ALGORITHM WITH FUELL NEWTON STEPS 162 7.5.3 THE
CLASSICAL ANALYSIS OF THE ALGORITHM 165 7.6 A VERSION OF THE ALGORITHM
WITH ADAPTIVE UPDATES 168 7.6.1 ADAPTIVE UPDATING 168 7.6.2 THE
PRIMAL-DUAL AFFINE-SCALING AND CENTERING DIRECTION 170 7.6.3 CONDITION
FOR ADAPTIVE UPDATES 172 7.6.4 CALCULATION OF THE ADAPTIVE UPDATE 172
7.6.5 SPECIAL CASE: ADAPTIVE UPDATE AT THE ^I-CENTER 174 7.6.6 A SIMPLE
VERSION OF THE CONDITION FOR ADAPTIVE UPDATING . . . . 175 7.6.7
ILLUSTRATION OF THE ALGORITHM WITH ADAPTIVE UPDATES 176 7.7 THE
PREDICTOR-CORRECTOR METHOD 177 7.7.1 THE PREDICTOR-CORRECTOR ALGORITHM
181 7.7.2 PROPERTIES OF THE AFFINE-SCALING STEP 181 7.7.3 ANALYSIS OF
THE PREDICTOR-CORRECTOR ALGORITHM 185 7.7.4 AN ADAPTIVE VERSION OF THE
PREDICTOR-CORRECTOR ALGORITHM . . . . 186 7.7.5 ILLUSTRATION OF ADAPTIVE
PREDICTOR-CORRECTOR ALGORITHM 188 7.7.6 QUADRATIC CONVERGENCE OF THE
PREDICTOR-CORRECTOR ALGORITHM . . 188 7.8 A VERSION OF THE ALGORITHM
WITH LARGE UPDATES 194 7.8.1 ESTIMATES OF BARRIER FUNCTION VALUES 196 X
CONTENTS 7.8.2 DECREASE OF BARRIER FUNCTION VALUE 199 7.8.3 A BOUND FOR
THE NUMBER OF INNER ITERATIONS 204 7.8.4 ILLUSTRATION OF THE ALGORITHM
WITH LARGE UPDATES 209 8 INITIALIZATION 213 III THE TARGET-FOLLOWING
APPROACH 217 9 PRELIMINARIES 219 9.1 INTRODUCTION 219 9.2 THE TARGET MAP
AND ITS INVERSE 221 9.3 TARGET SEQUENCES 226 9.4 THE TARGET-FOLLOWING
SCHEME 231 10 THE PRIMAL-DUAL NEWTON METHOD 235 10.1 INTRODUCTION 235
10.2 DEFINITION OF THE PRIMAL-DUAL NEWTON STEP 235 10.3 FEASIBILITY OF
THE PRIMAL-DUAL NEWTON STEP 236 10.4 PROXIMITY AND LOCAL QUADRATIC
CONVERGENCE 237 10.5 THE DAMPED PRIMAL-DUAL NEWTON METHOD 240 11
APPLICATIONS 247 11.1 INTRODUCTION 247 11.2 CENTRAL-PATH-FOLLOWING
METHOD 248 11.3 WEIGHTED-PATH-FOLLOWING METHOD 249 11.4 CENTERING METHOD
250 11.5 WEIGHTED-CENTERING METHOD 252 11.6 CENTERING AND OPTIMIZING
TOGETHER 254 11.7 ADAPTIVE AND LARGE TARGET-UPDATE METHODS 257 12 THE
DUAL NEWTON METHOD 259 12.1 INTRODUCTION 259 12.2 THE WEIGHTED DUAL
BARRIER FUNCTION 259 12.3 DEFINITION OF THE DUAL NEWTON STEP 261 12.4
FEASIBILITY OF THE DUAL NEWTON STEP 262 12.5 QUADRATIC CONVERGENCE 263
12.6 THE DAMPED DUAL NEWTON METHOD 264 12.7 DUAL TARGET-UPDATING 266 13
THE PRIMAL NEWTON METHOD 269 13.1 INTRODUCTION 269 13.2 THE WEIGHTED
PRIMAL BARRIER FUNCTION 270 13.3 DEFINITION OF THE PRIMAL NEWTON STEP
270 13.4 FEASIBILITY OF THE PRIMAL NEWTON STEP 272 13.5 QUADRATIC
CONVERGENCE 273 13.6 THE DAMPED PRIMAL NEWTON METHOD 273 13.7 PRIMAL
TARGET-UPDATING 275 CONTENTS XI 14 APPLICATION TO THE METHOD OF CENTERS
277 14.1 INTRODUCTION 277 14.2 DESCRIPTION OF RENEGAR S METHOD 278 14.3
TARGETS IN RENEGAR S METHOD 279 14.4 ANALYSIS OF THE CENTER METHOD 281
14.5 ADAPTIVE- AND LARGE-UPDATE VARIANTS OF THE CENTER METHOD 284 IV
MISCELLANEOUS TOPICS 287 15 KARMARKAR S PROJECTIVE METHOD 28 9 15.1
INTRODUCTION 289 15.2 THE UNIT SIMPLEX S N IN R N 290 15.3 THE
INNER-OUTER SPHERE BOUND 291 15.4 PROJECTIVE TRANSFORMATIONS OF E N 292
15.5 THE PROJECTIVE ALGORITHM 293 15.6 THE KARMARKAR POTENTIAL 295 15.7
ITERATION BOUND FOR THE PROJECTIVE ALGORITHM 297 15.8 DISCUSSION OF THE
SPECIAL FORMAT 297 15.9 EXPLICIT EXPRESSION FOR THE KARMARKAR SEARCH
DIRECTION 301 15.10THE HOMOGENEOUS KARMARKAR FORMAT 304 16 MORE
PROPERTIES OF THE CENTRAL PATH 307 16.1 INTRODUCTION 307 16.2
DERIVATIVES ALONG THE CENTRAL PATH 307 16.2.1 EXISTENCE OF THE
DERIVATIVES 307 16.2.2 BOUNDEDNESS OF THE DERIVATIVES 309 16.2.3
CONVERGENCE OF THE DERIVATIVES 314 16.3 ELLIPSOIDAL APPROXIMATIONS OF
LEVEL SETS 315 17 PARTIAL UPDATING 317 17.1 INTRODUCTION 317 17.2
MODIFIED SEARCH DIRECTION 319 17.3 MODIFIED PROXIMITY MEASURE 320 17.4
ALGORITHM WITH RANK-ONE UPDATES 323 17.5 COUNT OF THE RANK-ONE UPDATES
324 18 HIGHER-ORDER METHODS 329 18.1 INTRODUCTION 329 18.2 HIGHER-ORDER
SEARCH DIRECTIONS 330 18.3 ANALYSIS OF THE ERROR TERM 335 18.4
APPLICATION TO THE PRIMAL-DUAL DIKIN DIRECTION 337 18.4.1 INTRODUCTION
337 18.4.2 THE (FIRST-ORDER) PRIMAL-DUAL DIKIN DIRECTION 338 18.4.3
ALGORITHM USING HIGHER-ORDER DIKIN DIRECTIONS 341 18.4.4 FEASIBILITY AND
DUALITY GAP REDUCTION 341 18.4.5 ESTIMATE OF THE ERROR TERM 342 XII
CONTENTS 18.4.6 STEP SIZE 343 18.4.7 CONVERGENCE ANALYSIS 345 18.5
APPLICATION TO THE PRIMAL-DUAL LOGARITHMIC BARRIER METHOD 346 18.5.1
INTRODUCTION 346 18.5.2 ESTIMATE OF THE ERROR TERM 347 18.5.3 REDUCTION
OF THE PROXIMITY AFTER A HIGHER-ORDER STEP 349 18.5.4 THESTEP-SIZE 353
18.5.5 REDUCTION OF THE BARRIER PARAMETER 354 18.5.6 A HIGHER-ORDER
LOGARITHMIC BARRIER ALGORITHM 356 18.5.7 ITERATION BOUND 357 18.5.8
IMPROVED ITERATION BOUND 358 19 PARAMETRIC AND SENSITIVITY ANALYSIS 361
19.1 INTRODUCTION 361 19.2 PRELIMINARIES 362 19.3 OPTIMAL SETS AND
OPTIMAL PARTITION 362 19.4 PARAMETRIC ANALYSIS 366 19.4.1 THE
OPTIMAL-VALUE FUNCTION IS PIECEWISE LINEAR 368 19.4.2 OPTIMAL SETS ON A
LINEARITY INTERVAL 370 19.4.3 OPTIMAL SETS IN A BREAK POINT 372 19.4.4
EXTREME POINTS OF A LINEARITY INTERVAL 377 19.4.5 RUNNING THROUGH ALL
BREAK POINTS AND LINEARITY INTERVALS . . . . 379 19.5 SENSITIVITY
ANALYSIS 387 19.5.1 RANGES AND SHADOW PRICES 387 19.5.2 USING STRICTLY
COMPLEMENTARY SOLUTIONS 388 19.5.3 CLASSICAL APPROACH TO SENSITIVITY
ANALYSIS 391 19.5.4 COMPARISON OF THE CLASSICAL AND THE NEW APPROACH 394
19.6 CONCLUDING REMARKS 398 20 IMPLEMENTING INTERIOR POINT METHODS 40 1
20.1 INTRODUCTION 401 20.2 PROTOTYPE ALGORITHM 402 20.3 PREPROCESSING
405 20.3.1 DETECTING REDUNDANCY AND MAKING THE CONSTRAINT MATRIX SPARSER
406 20.3.2 REDUCING THE SIZE OF THE PROBLEM 407 20.4 SPARSE LINEAR
ALGEBRA 408 20.4.1 SOLVING THE AUGMENTED SYSTEM 408 20.4.2 SOLVING THE
NORMAL EQUATION 409 20.4.3 SECOND-ORDER METHODS 411 20.5 STARTING POINT
413 20.5.1 SIMPLIFYING THE NEWTON SYSTEM OF THE EMBEDDING MODEL . . . .
418 20.5.2 NOTES ON WARM START 418 20.6 PARAMETERS: STEP-SIZE, STOPPING
CRITERIA 419 20.6.1 TARGET-UPDATE 419 20.6.2 STEP SIZE 420 20.6.3
STOPPING CRITERIA 420 20.7 OPTIMAL BASIS IDENTIFICATION 421 CONTENTS
XIII 20.7.1 PRELIMINARIES 421 20.7.2 BASIS TABLEAU AND ORTHOGONALITY 422
20.7.3 THE OPTIMAL BASIS IDENTIFICATION PROCEDURE 424 20.7.4
IMPLEMENTATION ISSUES OF BASIS IDENTIFICATION 427 20.8 AVAILABLE
SOFTWARE 429 APPENDIX A SOME RESULTS FROM ANALYSIS 431 APPENDIX B
PSEUDO-INVERSE OF A MATRIX 433 APPENDIX C SOME TECHNICAL LEMMAS 435
APPENDIX D TRANSFORMATION TO CANONICAL FORM 445 D.L INTRODUCTION 445 D.2
ELIMINATION OF FREE VARIABLES 446 D.3 REMOVAL OF EQUALITY CONSTRAINTS
448 APPENDIX E THE DIKIN STEP ALGORITHM 451 E.L INTRODUCTION 451 E.2
SEARCH DIRECTION 451 E.3 ALGORITHM USING THE DIKIN DIRECTION 454 E.4
FEASIBILITY, PROXIMITY AND STEP-SIZE 455 E.5 CONVERGENCE ANALYSIS 458
BIBLIOGRAPHY 461 AUTHOR INDEX 479 SUBJECT INDEX 483 SYMBOL INDEX 495
|
any_adam_object | 1 |
author | Roos, Cornelis Terlaky, Tamás Vial, Jean-Philippe |
author_facet | Roos, Cornelis Terlaky, Tamás Vial, Jean-Philippe |
author_role | aut aut aut |
author_sort | Roos, Cornelis |
author_variant | c r cr t t tt j p v jpv |
building | Verbundindex |
bvnumber | BV020040943 |
callnumber-first | T - Technology |
callnumber-label | T57 |
callnumber-raw | T57.74 |
callnumber-search | T57.74 |
callnumber-sort | T 257.74 |
callnumber-subject | T - General Technology |
classification_rvk | SK 870 |
ctrlnum | (OCoLC)60500551 (DE-599)BVBBV020040943 |
dewey-full | 519.7/2 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.7/2 |
dewey-search | 519.7/2 |
dewey-sort | 3519.7 12 |
dewey-tens | 510 - Mathematics |
discipline | Mathematik |
edition | 2. ed. |
format | Book |
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id | DE-604.BV020040943 |
illustrated | Illustrated |
indexdate | 2024-07-09T20:11:29Z |
institution | BVB |
isbn | 0387263780 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-013362028 |
oclc_num | 60500551 |
open_access_boolean | |
owner | DE-824 DE-83 DE-11 DE-706 |
owner_facet | DE-824 DE-83 DE-11 DE-706 |
physical | XXIV, 497 S. graph. Darst. |
publishDate | 2006 |
publishDateSearch | 2006 |
publishDateSort | 2006 |
publisher | Springer |
record_format | marc |
spelling | Roos, Cornelis Verfasser aut Interior point methods for linear optimization by Cornelis Roos ; Tamás Terlaky ; Jean-Philippe Vial 2. ed. New York Springer 2006 XXIV, 497 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier 1. Aufl. u.d.T.: Roos, Cornelis: Theory and algorithms for linear optimization Algorithmes Innere-Punkte-Methode - Konvexe Optimierung swd Innere-Punkte-Methode - Lineare Optimierung swd Konvexe Optimierung - Innere-Punkte-Methode swd Lineare Optimierung - Innere-Punkte-Methode swd Optimisation mathématique Points intérieurs, Méthodes de Programação linear larpcal Programação matemática larpcal Programmation linéaire Algorithms Interior-point methods Linear programming Mathematical optimization Optimierung (DE-588)4043664-0 gnd rswk-swf Innere-Punkte-Methode (DE-588)4352322-5 gnd rswk-swf Lineare Optimierung (DE-588)4035816-1 gnd rswk-swf Konvexe Optimierung (DE-588)4137027-2 gnd rswk-swf Lineare Optimierung (DE-588)4035816-1 s Innere-Punkte-Methode (DE-588)4352322-5 s DE-604 Optimierung (DE-588)4043664-0 s Konvexe Optimierung (DE-588)4137027-2 s Terlaky, Tamás Verfasser aut Vial, Jean-Philippe Verfasser aut SWB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013362028&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Roos, Cornelis Terlaky, Tamás Vial, Jean-Philippe Interior point methods for linear optimization Algorithmes Innere-Punkte-Methode - Konvexe Optimierung swd Innere-Punkte-Methode - Lineare Optimierung swd Konvexe Optimierung - Innere-Punkte-Methode swd Lineare Optimierung - Innere-Punkte-Methode swd Optimisation mathématique Points intérieurs, Méthodes de Programação linear larpcal Programação matemática larpcal Programmation linéaire Algorithms Interior-point methods Linear programming Mathematical optimization Optimierung (DE-588)4043664-0 gnd Innere-Punkte-Methode (DE-588)4352322-5 gnd Lineare Optimierung (DE-588)4035816-1 gnd Konvexe Optimierung (DE-588)4137027-2 gnd |
subject_GND | (DE-588)4043664-0 (DE-588)4352322-5 (DE-588)4035816-1 (DE-588)4137027-2 |
title | Interior point methods for linear optimization |
title_auth | Interior point methods for linear optimization |
title_exact_search | Interior point methods for linear optimization |
title_full | Interior point methods for linear optimization by Cornelis Roos ; Tamás Terlaky ; Jean-Philippe Vial |
title_fullStr | Interior point methods for linear optimization by Cornelis Roos ; Tamás Terlaky ; Jean-Philippe Vial |
title_full_unstemmed | Interior point methods for linear optimization by Cornelis Roos ; Tamás Terlaky ; Jean-Philippe Vial |
title_short | Interior point methods for linear optimization |
title_sort | interior point methods for linear optimization |
topic | Algorithmes Innere-Punkte-Methode - Konvexe Optimierung swd Innere-Punkte-Methode - Lineare Optimierung swd Konvexe Optimierung - Innere-Punkte-Methode swd Lineare Optimierung - Innere-Punkte-Methode swd Optimisation mathématique Points intérieurs, Méthodes de Programação linear larpcal Programação matemática larpcal Programmation linéaire Algorithms Interior-point methods Linear programming Mathematical optimization Optimierung (DE-588)4043664-0 gnd Innere-Punkte-Methode (DE-588)4352322-5 gnd Lineare Optimierung (DE-588)4035816-1 gnd Konvexe Optimierung (DE-588)4137027-2 gnd |
topic_facet | Algorithmes Innere-Punkte-Methode - Konvexe Optimierung Innere-Punkte-Methode - Lineare Optimierung Konvexe Optimierung - Innere-Punkte-Methode Lineare Optimierung - Innere-Punkte-Methode Optimisation mathématique Points intérieurs, Méthodes de Programação linear Programação matemática Programmation linéaire Algorithms Interior-point methods Linear programming Mathematical optimization Optimierung Innere-Punkte-Methode Lineare Optimierung Konvexe Optimierung |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013362028&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT rooscornelis interiorpointmethodsforlinearoptimization AT terlakytamas interiorpointmethodsforlinearoptimization AT vialjeanphilippe interiorpointmethodsforlinearoptimization |