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Numerical PDE-Constrained Optimization [Pehme köide]

  • Formaat: Paperback / softback, 123 pages, kõrgus x laius: 235x155 mm, kaal: 2175 g, 2 Illustrations, color; 11 Illustrations, black and white; X, 123 p. 13 illus., 2 illus. in color., 1 Paperback / softback
  • Sari: SpringerBriefs in Optimization
  • Ilmumisaeg: 05-Mar-2015
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319133942
  • ISBN-13: 9783319133942
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  • Formaat: Paperback / softback, 123 pages, kõrgus x laius: 235x155 mm, kaal: 2175 g, 2 Illustrations, color; 11 Illustrations, black and white; X, 123 p. 13 illus., 2 illus. in color., 1 Paperback / softback
  • Sari: SpringerBriefs in Optimization
  • Ilmumisaeg: 05-Mar-2015
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319133942
  • ISBN-13: 9783319133942
Teised raamatud teemal:
This book introduces, in an accessible way, the basic elements of Numerical PDE-Constrained Optimization, from the derivation of optimality conditions to the design of solution algorithms. Numerical optimization methods in function-spaces and their application to PDE-constrained problems are carefully presented. The developed results are illustrated with several examples, including linear and nonlinear ones. In addition, MATLAB codes, for representative problems, are included. Furthermore, recent results in the emerging field of nonsmooth numerical PDE constrained optimization are also covered. The book provides an overview on the derivation of optimality conditions and on some solution algorithms for problems involving bound constraints, state-constraints, sparse cost functionals and variational inequality constraints.

Introduction.- Basic Theory of Partial Differential Equations and Their Discretization.- Theory of PDE-constrained Optimization.- Numerical Optimization Methods.- Box-constrained Problems.- Nonsmooth PDE-constrained Optimization.
1 Introduction
1(8)
1.1 Introductory Examples
1(3)
1.1.1 Optimal Heating
1(1)
1.1.2 Optimal Flow Control
2(1)
1.1.3 A Least Squares Parameter Estimation Problem in Meteorology
3(1)
1.2 A Class of Finite-Dimensional Optimization Problems
4(5)
2 Basic Theory of Partial Differential Equations and Their Discretization
9(16)
2.1 Notation and Lebesgue Spaces
9(1)
2.2 Weak Derivatives and Sobolev Spaces
10(3)
2.3 Elliptic Problems
13(7)
2.3.1 Poisson Equation
13(2)
2.3.2 A General Linear Elliptic Problem
15(1)
2.3.3 Nonlinear Equations of Monotone Type
16(4)
2.4 Discretization by Finite Differences
20(5)
3 Theory of PDE-Constrained Optimization
25(18)
3.1 Problem Statement and Existence of Solutions
25(2)
3.2 First Order Necessary Conditions
27(6)
3.2.1 Differentiability in Banach Spaces
27(3)
3.2.2 Optimality Condition
30(3)
3.3 Lagrangian Approach
33(5)
3.4 Second Order Sufficient Optimality Conditions
38(5)
4 Numerical Optimization Methods
43(26)
4.1 Descent Methods
44(9)
4.2 Newton's Method
53(7)
4.3 Quasi-Newton Methods
60(5)
4.4 Sequential Quadratic Programming (SQP)
65(4)
5 Box-Constrained Problems
69(22)
5.1 Problem Statement and Existence of Solutions
69(1)
5.2 Optimality Conditions
70(5)
5.3 Projection Methods
75(5)
5.4 Primal Dual Active Set Algorithm (PDAS)
80(6)
5.5 Semismooth Newton Methods (SSN)
86(5)
6 Nonsmooth PDE-Constrained Optimization
91(28)
6.1 Sparse L1-Optimization
91(5)
6.2 Pointwise State Constraints
96(5)
6.3 Variational Inequality Constraints
101(18)
6.3.1 Inequalities of the First Kind
103(7)
6.3.2 Inequalities of the Second Kind
110(9)
References 119(4)
Index 123
Juan Carlos De los Reyes is a Director of the Research Center on Mathematical Modelling (MODEMAT), and Professor of Optimization and Control at Escuela Politecnica Nacional.