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Trust Region Methods

Trust Region Methods


Part of MPS-SIAM Series on Optimization

  • Date Published: September 2000
  • availability: Available in limited markets only
  • format: Hardback
  • isbn: 9780898714609

£ 125.00

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About the Authors
  • This is the first comprehensive reference on trust-region methods, a class of numerical algorithms for the solution of nonlinear convex optimization methods. Its unified treatment covers both unconstrained and constrained problems and reviews a large part of the specialized literature on the subject. It also provides an up-to-date view of numerical optimization. Written primarily for postgraduates and researchers, the book features an extensive commented bibliography, which contains more than 1000 references by over 750 authors. The book also contains several practical comments and an entire chapter devoted to software and implementation issues. Its many illustrations, including nearly 100 figures, balance the formal and intuitive treatment of the presented topics.

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    Product details

    • Date Published: September 2000
    • format: Hardback
    • isbn: 9780898714609
    • length: 979 pages
    • dimensions: 261 x 183 x 50 mm
    • weight: 1.88kg
    • availability: Available in limited markets only
  • Table of Contents

    1. Introduction
    Part I. Preliminaries:
    2. Basic Concepts
    3. Basic Analysis and Optimality Conditions
    4. Basic Linear Algebra
    5. Krylov Subspace Methods
    Part II. Trust-Region Methods for Unconstrained Optimization:
    6. Global Convergence of the Basic Algorithm
    7.The Trust-Region Subproblem
    8. Further Convergence Theory Issues
    9. Conditional Models
    10. Algorithmic Extensions
    11. Nonsmooth Problems
    Part III. Trust-Region Methods for Constrained Optimization with Convex Constraints:
    12. Projection Methods for Convex Constraints
    13. Barrier Methods for Inequality Constraints
    Part IV. Trust-Region Mewthods for General Constained Optimization and Systems of Nonlinear Equations:
    14. Penalty-Function Methods
    15. Sequential Quadratic Programming Methods
    16. Nonlinear Equations and Nonlinear Fitting
    Part V. Final Considerations: Practicalities
    Appendix: A Summary of Assumptions
    Annotated Bibliography
    Subject and Notation Index
    Author Index.

  • Authors

    Andrew R. Conn, IBM T J Watson Research Center, New York

    Nicholas I. M. Gould

    Philippe L. Toint

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