Computational Issues in High Performance Software for Nonlinear Optimization

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.

List of contents

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.

Summary

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.

Product details

• Authors: Almerico Murli
• Assisted by: Almeric Murli (Editor), Almerico Murli (Editor), Toraldo (Editor), Toraldo (Editor), Gerardo Toraldo (Editor)
• Publisher: Springer Netherlands
• Languages: English
• Product format: Hardback
• Released: 23.11.2011
• EAN: 9780792398622
• ISBN: 978-0-7923-9862-2
• No. of pages: 158
• Dimensions: 155 mm x 235 mm x 11 mm
• Weight: 920 g
• Illustrations: IV, 158 p.
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous; Social sciences, law, business > Business > Management; Informatik, COMPUTERS / Computer Science, Lineare Programmierung, MATHEMATICS / Linear & Nonlinear Programming, BUSINESS & ECONOMICS / Operations Research, Mathematics