Computational Issues in High Performance Software for Nonlinear Optimization
Published on 31. January 1997
Book
Hardback
IV, 158 pages
978-0-7923-9862-2 (ISBN)
Description
Computational Issues in High Performance Software for Nonlinear
Research
brings together in one place important contributions and up-to-date research results in this important area.
Computational Issues in High Performance Software for Nonlinear Research serves as an excellent reference, providing insight into some of the most important research issues in the field.
Computational Issues in High Performance Software for Nonlinear Research serves as an excellent reference, providing insight into some of the most important research issues in the field.
More details
Edition
Reprinted from COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 7:1, 1997
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Research
Product notice
sewn/stitched
Cloth over boards
Illustrations
IV, 158 p.
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 11 mm
Weight
413 gr
ISBN-13
978-0-7923-9862-2 (9780792398622)
DOI
10.1007/b102245
Schweitzer Classification
Other editions
Additional editions
Almerico Murli | Gerardo Toraldo
Computational Issues in High Performance Software for Nonlinear Optimization
Book
03/2013
Springer
€160.49
Shipment within 15-20 days
Almerico Murli | Gerardo Toraldo
Computational Issues in High Performance Software for Nonlinear Optimization
E-Book
06/2007
Springer
€149.79
Available for download
Content
A Comparison of Large Scale Mixed Complementarity Problem Solvers.- Impact of Partial Separability on Large-Scale Optimization.- On the Number of Inner Iterations Per Outer Iteration of a Globally Convergent Algorithm for Optimization with General Nonlinear Inequality Constraints and Simple Bounds.- Numerical Experiences with New Truncated Newton Methods in Large Scale Unconstrained Optimization.- Sparse Linear Least Squares Problems in Optimization.- Simulated Annealing and Genetic Algorithms for the Facility Layout Problem: A Survey.- Sequential Quadratic Programming Methods for Large-Scale Problems.- A Scalable Parallel Interior Point Algorithm for Stochastic Linear Programming and Robust Optimization.