Please use this identifier to cite or link to this item:
|Title:||Applying a Newton method to strictly convex separable network quadratic programs|
|Authors:||Sun, J. |
|Keywords:||Network quadratic programming|
Piecewise quadratic programming
|Source:||Sun, J.,Kuo, H. (1998). Applying a Newton method to strictly convex separable network quadratic programs. SIAM Journal on Optimization 8 (3) : 728-745. ScholarBank@NUS Repository.|
|Abstract:||By introducing quadratic penalty terms, a strictly convex separable network quadratic program can be reduced to an unconstrained optimization problem whose objective is a continuously differentiable piecewise quadratic function. A recently developed nonsmooth version of Newton's method is applied to the reduced problem. The generalized Newton direction is computed by an iterative procedure which exploits the special network data structures that originated from the network simplex method. New features of the algorithm include the use of min-max bases and a dynamic strategy in computation of the Newton directions. Some preliminary computational results are presented. The results suggest the use of "warm start" instead of "cold start.".|
|Source Title:||SIAM Journal on Optimization|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 15, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.