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Lagrange Multiplier Approach to Variational Problems and Applications [Pehme köide]

  • Formaat: Paperback, 359 pages, kõrgus x laius x paksus: 229x152x19 mm, kaal: 660 g
  • Sari: Advances in Design and Control v. 15
  • Ilmumisaeg: 30-Jul-2008
  • Kirjastus: Society for Industrial & Applied Mathematics,U.S.
  • ISBN-10: 0898716497
  • ISBN-13: 9780898716498
Teised raamatud teemal:
  • Formaat: Paperback, 359 pages, kõrgus x laius x paksus: 229x152x19 mm, kaal: 660 g
  • Sari: Advances in Design and Control v. 15
  • Ilmumisaeg: 30-Jul-2008
  • Kirjastus: Society for Industrial & Applied Mathematics,U.S.
  • ISBN-10: 0898716497
  • ISBN-13: 9780898716498
Teised raamatud teemal:
Lagrange multiplier theory provides a tool for the analysis of a general class of nonlinear variational problems and is the basis for developing efficient and powerful iterative methods for solving these problems. This comprehensive monograph analyzes Lagrange multiplier theory and shows its impact on the development of numerical algorithms for problems posed in a function space setting. The book is motivated by the idea that a full treatment of a variational problem in function spaces would not be complete without a discussion of in nite-dimensional analysis, proper discretization, and the relationship between the two. The authors develop and analyze efficient algorithms for constrained optimization and convex optimization problems based on the augumented Lagrangian concept and cover such topics as sensitivity analysis, convex optimization, second order methods, and shape sensitivity calculus. General theory is applied to challenging problems in optimal control of partial differential equations, image analysis, mechanical contact and friction problems, and American options for the Black-Scholes model.
Preface xi
Existence of Lagrange Multipliers
1(26)
Problem statement and generalities
1(2)
A generalized open mapping theorem
3(2)
Regularity and existence of Lagrange multipliers
5(3)
Applications
8(9)
Weakly singular problems
17(6)
Approximation, penalty, and adapted penalty techniques
23(4)
Approximation techniques
23(1)
Penalty techniques
24(3)
Sensitivity Analysis
27(38)
Generalities
27(4)
Implicit function theorem
31(3)
Stability results
34(11)
Lipschitz continuity
45(8)
Differentiability
53(9)
Application to optimal control of an ordinary differential equation
62(3)
First Order Augmented Lagrangians for Equality and Finite Rank Inequality Constraints
65(22)
Generalities
65(2)
Augmentability and sufficient optimality
67(8)
The first order augmented Lagrangian algorithm
75(3)
Convergence of Algorithm ALM
78(4)
Application to a parameter estimation problem
82(5)
Augmented Lagrangian Methods for Nonsmooth, Convex Optimization
87(42)
Introduction
87(2)
Convex analysis
89(9)
Conjugate and biconjugate functionals
92(3)
Subdifferential
95(3)
Fenchel duality theory
98(6)
Generalized Yosida-Moreau approximation
104(5)
Optimality systems
109(5)
Augmented Lagrangian method
114(5)
Applications
119(10)
Bingham flow
120(1)
Image restoration
121(1)
Elastoplastic problem
122(1)
Obstacle problem
122(2)
Signorini problem
124(1)
Friction problem
125(1)
L1-fitting
126(1)
Control problem
126(3)
Newton and SQP Methods
129(26)
Preliminaries
129(4)
Newton method
133(4)
SQP and reduced SQP methods
137(6)
Optimal control of the Navier-Stokes equations
143(5)
Necessary optimality condition
145(2)
Sufficient optimality condition
147(1)
Newton's method for (5.4.1)
147(1)
Newton method for the weakly singular case
148(7)
Augmented Lagrangian-SQP Methods
155(34)
Generalities
155(1)
Equality-constrained problems
156(9)
Partial elimination of constraints
165(7)
Applications
172(11)
An introductory example
172(2)
A class of nonlinear elliptic optimal control problems
174(9)
Approximation and mesh-independence
183(3)
Comments
186(3)
The Primal-Dual Active Set Method
189(26)
Introduction and basic properties
189(7)
Monotone class
196(1)
Cone sum preserving class
197(3)
Diagonally dominated class
200(2)
Bilateral constraints, diagonally dominated class
202(4)
Nonlinear control problems with bilateral constraints
206(9)
Semismooth Newton Methods I
215(38)
Introduction
215(2)
Semismooth functions in finite dimensions
217(17)
Basic concepts and the semismooth Newton algorithm
217(5)
Globalization
222(3)
Descent directions
225(3)
A Gauss-Newton algorithm
228(3)
A nonlinear complementarity problem
231(3)
Semismooth functions in infinite-dimensional spaces
234(6)
The primal-dual active set method as a semismooth Newton method
240(3)
Semismooth Newton methods for a class of nonlinear complementarity problems
243(3)
Semismooth Newton methods and regularization
246(7)
Semismooth Newton Methods II: Applications
253(24)
BV-based image restoration problems
254(9)
Friction and contact problems in elasticity
263(14)
Generalities
263(2)
Contact problem with Tresca friction
265(7)
Contact problem with Coulomb friction
272(5)
Parabolic Variational Inequalities
277(28)
Strong solutions
281(10)
Regularity
291(1)
Continuity of q → y(q) ε L∞ (Ω)
292(5)
Difference schemes and weak solutions
297(5)
Monotone property
302(3)
Shape Optimization
305(22)
Problem statement and generalities
305(3)
Shape derivative
308(6)
Examples
314(13)
Elliptic Dirichlet boundary value problem
314(2)
Inverse interface problem
316(5)
Elliptic systems
321(2)
Navier-Stokes system
323(4)
Bibliography 327(12)
Index 339
Kazufumi Ito is Professor in the Department of Mathematics and an affiliate of the Center for Research in Scientific Computation at North Carolina State University. He was co-recipient of the SIAM Outstanding Paper Award in 2006. Karl Kunisch is Professor in the Institute of Mathematics at the University of Graz, Austria. He was co-recipient of the SIAM Outstanding Paper Award in 2006.