DocumentCode
306728
Title
A reduced-complexity bundle method for maximizing concave nonsmooth functions
Author
Tomastik, Robert N. ; Luh, Peter B. ; Zhang, Daoyuan
Author_Institution
United Technol. Res. Center, East Hartford, CT, USA
Volume
2
fYear
1996
fDate
11-13 Dec 1996
Firstpage
2114
Abstract
Bundle methods have emerged as a promising concept for maximizing nonsmooth concave functions of many variables. A computationally-expensive step in conventional bundle methods is to find a trial direction, and current methods have exponential complexity, making them impractical for large problems. In this paper, a new version of the bundle method is developed, and this method has polynomial complexity in computing a trial direction
Keywords
computational complexity; concave programming; mathematical programming; concave nonsmooth function maximization; polynomial complexity; reduced-complexity bundle method; Convergence; Job shop scheduling; Lagrangian functions; Manufacturing; Mathematics; Polynomials; Processor scheduling; Scheduling algorithm; Silver; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location
Kobe
ISSN
0191-2216
Print_ISBN
0-7803-3590-2
Type
conf
DOI
10.1109/CDC.1996.572917
Filename
572917
Link To Document