The book



Andrew R. Conn, Nicholas I. M. Gould and 
Philippe L. Toint



was published by SIAM, Philadelphia,
in the MPS/SIAM Series on Optimization,
in August 2000.

A number of errata and updates have been reported. Here is the current list (Postscript, PDF).

The complete LaTeX
together with more recent papers on the subject, is available.

SIAM Publicity blurb (corrected):

This is the first comprehensive reference on trust-region methods, a class of algorithms for the solution of nonlinear nonconvex optimization problems. It is a unified treatment that covers both unconstrained and constrained problems, including many specialised topics and reviews of the literature not easily obtained elsewhere.

Written primarily for post-graduates and researchers, the book features an extensive commented bibliography, which contains 972 references by 745 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, helps to make the formal and in-depth treatment of the presented topics more accessible.

About the Authors:
Andrew Conn is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Nick Gould works in the Numerical Analysis Group in the Computational Science and Engineering Department at the Rutherford Appleton Laboratory in Oxfordshire, England. He was awarded the Leslie Fox prize in Numerical Analysis in 1986. He serves on the editorial boards of the SIAM Journal on Optimization and the MPS journal Mathematical Programming. Philippe Toint is a Professor in the Department of Mathematics, Founder and Director of the Transportation Research Group, and Head of the University Computing Services at the University of Namur in Belgium. He also serves on the editorial boards of Operations Research and Transportation Science. All three authors were corecipients of the 1994 Beale-Orchard-Hays prize for their work on the LANCELOT optimization package.

Preface; Chapter 1: Introduction; PART I: PRELIMINARIES. Chapter 2: Basic Concepts; Chapter 3: Basic Analysis and Optimality Conditions; Chapter 4: Basic Linear Algebra; Chapter 5 Krylov Subspace Methods; PART II: TRUST-REGION METHODS FOR UNCONSTRAINED OPTIMIZATION. Chapter 6: Global Convergence of the Basic Algorithm; Chapter 7: The Trust-Region Subproblem; Chapter 8: Further Convergence Theory Issues; Chapter 9: Conditional Models; Chapter 10: Algorithmic Extensions; Chapter 11: Nonsmooth Problems; PART III: TRUST-REGION METHODS FOR CONSTRAINED OPTIMIZATION WITH CONVEX CONSTRAINTS. Chapter 12: Projection Methods for Convex Constraints; 13: Barrier Methods for Inequality Constraints; PART IV: TRUST-REGION METHODS FOR GENERAL CONSTRAINED OPTIMIZATION AND SYSTEMS OF NONLINEAR EQUATIONS. Chapter 14: Penalty-Function Methods; Chapter 15: Sequential Quadratic Programming Methods; Chapter 16: Nonlinear Equations and Nonlinear Fitting; PART V: FINAL CONSIDERATIONS. Chapter 17: Practicalities; Afterword; Appendix: A Summary of Assumptions; Annotated Bibliography; Subject and Notation Index; Author Index.

Available August 2000 / Approx. 951 pages / Hardcover / ISBN 0-89871-460-5 / Order Code MP01

Also available from