Nonlinear programming 4 : proceedings of the Nonlinear Programming Symposium 4 /
Clasificación: | Libro Electrónico |
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Autores Corporativos: | , |
Otros Autores: | , , |
Formato: | Electrónico Congresos, conferencias eBook |
Idioma: | Inglés |
Publicado: |
Burlington :
Academic Press/Elsevier Science,
[2014], ©1981.
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Temas: | |
Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Chapter 3. qp-basedmethods for large-scale nonlinearly constrained optimizationabstract; 1. introduction; 2. large-scale linearly constrained optimization; 3. qp-based methods for dense problems; 4. the use of a linearly constrained subproblem; 5. extension of qp-based methods to the large-scale case; 6. representing the basis inverse; 7. the search direction for the superbasic variables; 8. an inequality qpapproach; 9. conclusions; references; chapter 4. numerical experiments with an exact l1penalty function method; abstract; 1. introduction; 2. a globally convergent algorithm.
- 3. an active set method4. numerical experiments and discussion; acknowledgments; references; chapter 5. an iterative linear programming algorithmbased on an augmented lagrangian; abstract; references; chapter 6. iterative algorithmsfor singular minimization problems; abstract; 1. introduction; 2. the quadratic case; 3. nonquadratic case; 4. minimization in the presence of errors; conclusions; acknowledgments; references; chapter 7. a new derivation of symmetricpositive definite secant updates; abstract; 1. introduction and background; 2. the bfgs and dfp from the good and bad broyden methods.
- 3. hereditary positive definiteness and iren sizing forsymmetric rank-two updates4. a projected bfgs from the projected broyden update; 5. updating cholesky factors; references; appendix: the scaled bfgs derivation; chapter8. on preconditioned conjugate gradient methods; abstract; i. introduction; ii. using moderate additional storage; iii. utilizing sparse second order information; references; chapter 9. finding the global minimum of a function of one variable using the method of constantsigned higher order derivatives; abstract; 1. introduction; 2. preliminary theorems and lemmas.
- 3. algorithmic considerations4. application to polynomial minimization; 5. effects of calculation errors; 6. comment; references; chapter 10. on a bundle algorithmfor nonsmooth optimization; abstract; 1. introduction; 2. the algorithm without constraints; 3. linearly constrained problems; appendix; references; chapter 11. convergence results in a class ofvariable metric subgradient methods1; abstract; 1. introduction; 2. examples; 3. a class of variable metric subgradient optimizationmethods; 4. various methods; 5. behaviour on systems of linear equalities and onquadratics; 6. experiments.