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.
Introduction; A. Murli, G. Toraldo. A Comparison of Large Scale Mixed Complimentarity Problem Solvers; S.C. Billups, et al. Impact of Partial Separability on Large Scale Optimization; A. Bouaricha, J.J. More. On the Number of Inner Iterations Per Outer Iteration of a Globally Convergent Algorithm with General Nonlinear Inequality Constraints and Simple Bounds; A.R. Conn, et al. Numerical Experiences with New Truncated Newton Methods in Large Scale Unconstrained Optimization; S. Lucidi, M. Roma. Sparse Linear Least Squares Problems in Optimization; P. Matstoms. Simulated Annealing and Genetic Algorithms for the Facility Layout problem: A Survey; T.D. Mavridou, P.M. Pardalos. Sequential Quadratic Programming Methods for Large-Scale Problems; W. Murray. A Scalable Parallel Interior Point Algorithm for Stochastic Linear Programming and Robust Optimization; Dafeng Yang, S.A. Zenios.
Number Of Pages: 158
Published: December 2009
Publisher: SPRINGER VERLAG GMBH
Country of Publication: NL
Dimensions (cm): 23.39 x 15.6
Weight (kg): 0.41