Jean Bernard Lasserre
An Introduction to Polynomial and Semi-Algebraic Optimization
Jean Bernard Lasserre
An Introduction to Polynomial and Semi-Algebraic Optimization
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The first comprehensive introduction to the powerful moment approach for solving global optimization problems.
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The first comprehensive introduction to the powerful moment approach for solving global optimization problems.
Produktdetails
- Produktdetails
- Verlag: Cambridge University Press
- Seitenzahl: 354
- Erscheinungstermin: 2. April 2015
- Englisch
- Abmessung: 235mm x 157mm x 24mm
- Gewicht: 666g
- ISBN-13: 9781107060579
- ISBN-10: 1107060575
- Artikelnr.: 41786374
- Verlag: Cambridge University Press
- Seitenzahl: 354
- Erscheinungstermin: 2. April 2015
- Englisch
- Abmessung: 235mm x 157mm x 24mm
- Gewicht: 666g
- ISBN-13: 9781107060579
- ISBN-10: 1107060575
- Artikelnr.: 41786374
Jean Bernard Lasserre is Directeur de Recherche at the LAAS laboratory in Toulouse and a member of the Institute of Mathematics of Toulouse (IMT). In 2009 he received the Lagrange Prize, awarded jointly by the Mathematical Optimization Society (MOS) and the Society for Industrial and Applied Mathematics (SIAM). He is the winner of the 2015 INFORMS Optimization Society Khachiyan Prize, awarded for life-time achievements in the area of optimization.
Preface
List of symbols
1. Introduction and messages of the book
Part I. Positive Polynomials and Moment Problems: 2. Positive polynomials and moment problems
3. Another look at nonnegativity
4. The cone of polynomials nonnegative on K
Part II. Polynomial and Semi-algebraic Optimization: 5. The primal and dual points of view
6. Semidefinite relaxations for polynomial optimization
7. Global optimality certificates
8. Exploiting sparsity or symmetry
9. LP relaxations for polynomial optimization
10. Minimization of rational functions
11. Semidefinite relaxations for semi-algebraic optimization
12. An eigenvalue problem
Part III. Specializations and Extensions: 13. Convexity in polynomial optimization
14. Parametric optimization
15. Convex underestimators of polynomials
16. Inverse polynomial optimization
17. Approximation of sets defined with quantifiers
18. Level sets and a generalization of the Löwner-John's problem
Appendix A. Semidefinite programming
Appendix B. The GloptiPoly software
References
Index.
List of symbols
1. Introduction and messages of the book
Part I. Positive Polynomials and Moment Problems: 2. Positive polynomials and moment problems
3. Another look at nonnegativity
4. The cone of polynomials nonnegative on K
Part II. Polynomial and Semi-algebraic Optimization: 5. The primal and dual points of view
6. Semidefinite relaxations for polynomial optimization
7. Global optimality certificates
8. Exploiting sparsity or symmetry
9. LP relaxations for polynomial optimization
10. Minimization of rational functions
11. Semidefinite relaxations for semi-algebraic optimization
12. An eigenvalue problem
Part III. Specializations and Extensions: 13. Convexity in polynomial optimization
14. Parametric optimization
15. Convex underestimators of polynomials
16. Inverse polynomial optimization
17. Approximation of sets defined with quantifiers
18. Level sets and a generalization of the Löwner-John's problem
Appendix A. Semidefinite programming
Appendix B. The GloptiPoly software
References
Index.
Preface
List of symbols
1. Introduction and messages of the book
Part I. Positive Polynomials and Moment Problems: 2. Positive polynomials and moment problems
3. Another look at nonnegativity
4. The cone of polynomials nonnegative on K
Part II. Polynomial and Semi-algebraic Optimization: 5. The primal and dual points of view
6. Semidefinite relaxations for polynomial optimization
7. Global optimality certificates
8. Exploiting sparsity or symmetry
9. LP relaxations for polynomial optimization
10. Minimization of rational functions
11. Semidefinite relaxations for semi-algebraic optimization
12. An eigenvalue problem
Part III. Specializations and Extensions: 13. Convexity in polynomial optimization
14. Parametric optimization
15. Convex underestimators of polynomials
16. Inverse polynomial optimization
17. Approximation of sets defined with quantifiers
18. Level sets and a generalization of the Löwner-John's problem
Appendix A. Semidefinite programming
Appendix B. The GloptiPoly software
References
Index.
List of symbols
1. Introduction and messages of the book
Part I. Positive Polynomials and Moment Problems: 2. Positive polynomials and moment problems
3. Another look at nonnegativity
4. The cone of polynomials nonnegative on K
Part II. Polynomial and Semi-algebraic Optimization: 5. The primal and dual points of view
6. Semidefinite relaxations for polynomial optimization
7. Global optimality certificates
8. Exploiting sparsity or symmetry
9. LP relaxations for polynomial optimization
10. Minimization of rational functions
11. Semidefinite relaxations for semi-algebraic optimization
12. An eigenvalue problem
Part III. Specializations and Extensions: 13. Convexity in polynomial optimization
14. Parametric optimization
15. Convex underestimators of polynomials
16. Inverse polynomial optimization
17. Approximation of sets defined with quantifiers
18. Level sets and a generalization of the Löwner-John's problem
Appendix A. Semidefinite programming
Appendix B. The GloptiPoly software
References
Index.