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Nesterov Y., Nemirovskii A. — Interior-Point Polynomial Algorithms in Convex Programming
Nesterov Y., Nemirovskii A. — Interior-Point Polynomial Algorithms in Convex Programming



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Название: Interior-Point Polynomial Algorithms in Convex Programming

Авторы: Nesterov Y., Nemirovskii A.

Аннотация:

Written for specialists working in optimization, mathematical programming, or control theory. The general theory of path-following and potential reduction interior point polynomial time methods, interior point methods, interior point methods for linear and quadratic programming, polynomial time methods for nonlinear convex programming, efficient computation methods for control problems and variational inequalities, and acceleration of path-following methods are covered. In this book, the authors describe the first unified theory of polynomial-time interior-point methods. Their approach provides a simple and elegant framework in which all known polynomial-time interior-point methods can be explained and analyzed; this approach yields polynomial-time interior-point methods for a wide variety of problems beyond the traditional linear and quadratic programs.

The book contains new and important results in the general theory of convex programming, e.g., their "conic" problem formulation in which duality theory is completely symmetric. For each algorithm described, the authors carefully derive precise bounds on the computational effort required to solve a given family of problems to a given precision. In several cases they obtain better problem complexity estimates than were previously known. Several of the new algorithms described in this book, e.g., the projective method, have been implemented, tested on "real world" problems, and found to be extremely efficient in practice.

Special Features o the developed theory of polynomial methods covers all approaches known so far o presents detailed descriptions of algorithms for many important classes of nonlinear problems

Audience Specialists working in the areas of optimization, mathematical programming, or control theory will find this book invaluable for studying interior-point methods for linear and quadratic programming, polynomial-time methods for nonlinear convex programming, and efficient computational methods for control problems and variational inequalities. A background in linear algebra and mathematical programming is necessary to understand the book. The detailed proofs and lack of "numerical examples" might suggest that the book is of limited value to the reader interested in the practical aspects of convex optimization, but nothing could be further from the truth. An entire chapter is devoted to potential reduction methods precisely because of their great efficiency in practice.

Contents Chapter 1: Self-Concordant Functions and Newton Method; Chapter 2: Path-Following Interior-Point Methods; Chapter 3: Potential Reduction Interior-Point Methods; Chapter 4: How to Construct Self-Concordant Barriers; Chapter 5: Applications in Convex Optimization; Chapter 6: Variational Inequalities with Monotone Operators; Chapter 7: Acceleration for Linear and Linearly Constrained Quadratic Problems; Bibliography; Appendix 1; Appendix 2.



Язык: en

Рубрика: Computer science/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 1994

Количество страниц: 416

Добавлена в каталог: 12.12.2013

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Acceleration for linear and linearly constrained quadratic problems, main inequality      323
Acceleration for linear and linearly constrained quadratic problems, strategy      316
Acceleration for linear and linearly constrained quadratic problems, tactics      317
Advanced linear algebra      321
Barrier calculus      148 174
Barrier-generated family      2
Barrier-generated family, Legendre transformation      181
Barrier-generated family, superposition theorem      182 184
Boolean programming, dual bounds for      243
Combination rules for barriers/coverings, arithmetic summation      155
Combination rules for barriers/coverings, conic hull      149
Combination rules for barriers/coverings, direct products      149
Combination rules for barriers/coverings, images under affine mappings      152
Combination rules for barriers/coverings, intersections      149
Combination rules for barriers/coverings, inverse images under affine mappings      148
Combination rules for barriers/coverings, inverse images under nonlinear mappings      156
Combination rules for barriers/coverings, projective transformation      143
Combined volumetric barrier      203 246
Complementarity problem      277 381
Conic duality      103
Conic representation      175
Conic representation, second-order      224
Conic representation, second-order, examples      226
Constraint regularization scheme      218
Convex problem, conic form      102 147 188
Convex problem, conic form, complementary slackness relation      104 106 109
Convex problem, conic form, dual formulation      103
Convex problem, conic form, dual inequality      105
Convex problem, conic form, duality relations      105
Convex problem, conic form, duality theorem      109
Convex problem, conic form, normal primal-dual pair      106
Convex problem, conic form, primal-dual pair      104
Convex problem, conic form, primal-dual relations      107
Convex problem, conic form, zero duality gap      106 109
Convex problem, standard form      57 103 147 188
Convex-concave games      276
Coverings      175
Coverings, calculus      176
Coverings, calculus, direct product      178
Coverings, calculus, images      176
Coverings, calculus, intersections      178
Coverings, calculus, inverse images      176
Curvature condition      383
Differential inclusion      245
Dikin's ellipsoid      13 34
Dikin's method      379
Duality theorem      109
Eigenvalues minimization problems, largest of      239 242
Eigenvalues minimization problems, sum of k largest      239
Extremal ellipsoids, circumscribing minimal volume ellipsoid      270
Extremal ellipsoids, inscribing maximal volume ellipsoid      244 249
Extremal ellipsoids, inscribing maximal volume ellipsoid, algebraic formulation      250
Extremal ellipsoids, inscribing maximal volume ellipsoid, geometric formulation      249
Extremal ellipsoids, inscribing maximal volume ellipsoid, path-following method for finding      252 254 257 263 268 270
Function, $\beta$-compatible with self-concordant barrier      66
Function, fractional-quadratic      227 241
Function, Lyapunov's      101
Function, positive-semidefinite representable      237
Function, potential      101 112 124 139
Functional element      176
Functional element, Legendre transformation of      181
Linear differential equations, uniqueness theorem      14
Linear-fractional problems      121
Logarithmically homogeneous barriers, $\nu$-normal      40
Logarithmically homogeneous barriers, definition of      39
Logarithmically homogeneous barriers, Legendre transformation of      47 48
Logarithmically homogeneous barriers, main properties of      40 41
Lovasz capacity number of graph      242
Mappings, compatible with barrier      160
Mappings, compatible with convex domain      159
Mappings, compatible with convex domain, compatibility of superpositions      168
Mappings, compatible with convex domain, examples      160 165
Mappings, concave with respect to cone      156
Mappings, concave with respect to cone, examples      157
Mappings, maximal monotone      274
Mappings, monotone      273
Mappings, quadratic-fractional      166
Methods of centers      2 82 see "Potential
Methods, barrier-generated      2 70
Methods, interior penalty function      1 379
Monotone element      274
Monotone element, potential      310
Monotone element, transformation rules for      311—313
Monotone operator, compatible with self-concordant barrier, definition of      291
Monotone operator, compatible with self-concordant barrier, properties of      291 292
Monotone operator, convex representation of      307
Monotone operator, linear monotone      304
Multistep barrier methods, acceleration based on optimal method for smooth convex optimization, efficiency estimate      336
Multistep barrier methods, acceleration based on optimal method for smooth convex optimization, scheme      334
Multistep barrier methods, conjugate-gradient-based acceleration, efficiency estimate      351
Multistep barrier methods, conjugate-gradient-based acceleration, scheme      348
Multistep barrier methods, fixed-point-based acceleration, efficiency estimate      342
Multistep barrier methods, fixed-point-based acceleration, scheme      340
Multistep barrier methods, gradient-descent-based acceleration, efficiency estimate      330
Multistep barrier methods, gradient-descent-based acceleration, scheme      329
Multistep barrier methods, sets $K_{\alpha}(x)$      327
Nash equilibrium      276
Newton decrement, definition of      15 284
Newton decrement, properties of      16
Newton iterate      16 284
Newton method, convergence results      17 18 24
Newton method, damped      15
Newton method, stepsize rules      24 26
Path-following interior-point methods      57
Path-following interior-point methods, barrier-generated      65 68
Path-following interior-point methods, barrier-generated, efficiency estimate      75
Path-following interior-point methods, barrier-generated, large-step strategy      76
Path-following interior-point methods, barrier-generated, main stage      73
Path-following interior-point methods, barrier-generated, preliminary stage      70
Path-following interior-point methods, dual parallel trajectories method      86 87
Path-following interior-point methods, dual parallel trajectories method, efficiency estimate      92
Path-following interior-point methods, dual parallel trajectories method, scheme      90 91
Path-following interior-point methods, method of centers      80
Path-following interior-point methods, method of centers, efficiency estimate      84
Path-following interior-point methods, method of centers, scheme      84
Path-following interior-point methods, primal parallel trajectories method      93
Path-following interior-point methods, primal parallel trajectories method, efficiency estimate      96 99
Path-following interior-point methods, primal parallel trajectories method, scheme      95
Path-following scheme      2 57
Perturbed primal problem, cost function      106
Perturbed primal problem, properties of      106
Polynomial-time methods, definition for LP      3
Polynomial-time methods, definition for NLP      5
Polynomial-time methods, historical remarks      380
Positive-semidefinite representation      237
Positive-semidefinite representation of determinant      240
Positive-semidefinite representation of Euclidean norm      238
Positive-semidefinite representation of fractional-quadratic function      241
Positive-semidefinite representation of geometric mean      240
Positive-semidefinite representation of matrix norm      238
Positive-semidefinite representation of maximal eigenvalue      239
Positive-semidefinite representation of quadratic-functional      238
Positive-semidefinite representation of sum of k largest eigenvalues      239
Potential reduction interior-point methods      101
Potential reduction interior-point methods, anticipated behaviour      248 381
Potential reduction interior-point methods, Karmarkar method      111
Potential reduction interior-point methods, Karmarkar method, assumptions      111
Potential reduction interior-point methods, Karmarkar method, potential function for      112
Potential reduction interior-point methods, Karmarkar method, projective transformation-based explanation of      116
Potential reduction interior-point methods, Karmarkar method, rate of convergence      115
Potential reduction interior-point methods, Karmarkar method, scheme      114
Potential reduction interior-point methods, Karmarkar method, sliding objective approach      119
Potential reduction interior-point methods, Karmarkar method, unknown optimal value      117
Potential reduction interior-point methods, primal-dual method      138
Potential reduction interior-point methods, primal-dual method, assumptions      138
Potential reduction interior-point methods, primal-dual method, large-step strategy      145
Potential reduction interior-point methods, primal-dual method, potential function      139
Potential reduction interior-point methods, primal-dual method, rate of convergence      144
Potential reduction interior-point methods, primal-dual method, scheme      140
Potential reduction interior-point methods, projective method      121
Potential reduction interior-point methods, projective method, assumptions      121 123
Potential reduction interior-point methods, projective method, large-step strategy      135
Potential reduction interior-point methods, projective method, potential function      124
Potential reduction interior-point methods, projective method, rate of convergence      130 132
Potential reduction interior-point methods, projective method, scheme      126—130
Preconditioned conjugate gradients method      346
Problems, approximation in $L_{p}$-norm      232
Problems, arising in control theory      245
Problems, complementarity      277 381
Problems, conic involving second-order cone      223
Problems, geometrical programming      230
Problems, inscribing maximal ellipsoid into polytope      244
Problems, minimization of largest eigenvalue      242
Problems, minimization of matrix norm      234 242
Problems, quadratically constrained quadratic      220 241 381
Problems, quadratically constrained quadratic, path-following approach      220
Problems, quadratically constrained quadratic, potential-reduction approach      221
Problems, reducible to inequality with monotone operator      275
Problems, semidefinite programming      236
Pure exchange model of Arrow — Debreu      302
Recessive cone      45
Recessive subspace      15
Relative Lipschitz condition      383
Second-order representation      224
Second-order representation, Euclidean norm      226
Second-order representation, fractional-quadratic function      227
Second-order representation, geometrical mean      226
Second-order representation, quadratic functional      226
Self-concordance      12
Self-concordant barrier      3
Self-concordant barrier for cone of positive-semidefinite symmetric matrices      198
Self-concordant barrier for epigraph of entropy function      192
Self-concordant barrier for epigraph of exponent      193
Self-concordant barrier for epigraph of fractional-quadratic function      201
Self-concordant barrier for epigraph of functions of Euclidean norm      195
Self-concordant barrier for epigraph of logarithm      193
Self-concordant barrier for epigraph of matrix norm      199
Self-concordant barrier for epigraph of power function      191 192
Self-concordant barrier for piecewise-quadratically bounded domains      194
Self-concordant barrier for polytope      193 203
Self-concordant barrier for second-order cone      195
Self-concordant barrier, bounds on parameter      42 49
Self-concordant barrier, definition of      32
Self-concordant barrier, examples      33 40 81
Self-concordant barrier, Legendre transformation      45 47 86
Self-concordant barrier, main properties      33 34 39
Self-concordant barrier, parameter of      4 32
Self-concordant families      58
Self-concordant families, barrier-generated      66
Self-concordant families, center-generated      80
Self-concordant families, definition of      58
Self-concordant families, homogeneous      86
Self-concordant families, metric associated with      61
Self-concordant families, properties      58 59 62
Self-concordant function, behaviour on Lebesgue set      27—29
Self-concordant function, definition of      12
Self-concordant function, Legendre transformation      43
Self-concordant function, main properties      12 13
Self-concordant function, strongly      12
Self-concordant monotone operator, definition of      280
Self-concordant monotone operator, Newton decrement      284
Self-concordant monotone operator, Newton method      286
Self-concordant monotone operator, properties      280 282 283 285
Semidefinite programming      236
Standard logarithmic barrier      2 315
Symmetric k-linear form      361
Uniqueness theorem for linear differential equations      14
Universal barrier      49
Variational inequalities      273
Variational inequalities, accuracy measure      294 299
Variational inequalities, accuracy of approximation      298
Variational inequalities, application example      302 365
Variational inequalities, barrier-generated family of      294
Variational inequalities, path-following method for      290
Variational inequalities, path-following method for, efficiency estimate      302
Variational inequalities, path-following method for, initialization      296
Variational inequalities, path-following method for, summary      301
Variational inequalities, path-following method for, updating rule      295
Variational inequalities, reduction to convex program      305
Variational inequalities, regularity      305
Variational inequalities, with linear monotone operator      304
Volumetric barrier      203
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