DocumentCode
3338222
Title
A superlinearly convergent algorithm for min-max problems
Author
Polak, E. ; Mayne, D.Q. ; Higgins, J.E.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
fYear
1989
fDate
13-15 Dec 1989
Firstpage
894
Abstract
Algorithms for solving the problem of minimizing the maximum of a finite number of functions are proposed and analyzed. Quadratic approximations to the functions are used in determination of a search direction. Global convergence is proved, and it is shown that the rate of convergence is quadratic in the convex case and superlinear in the nonconvex case
Keywords
approximation theory; convergence of numerical methods; minimax techniques; search problems; global convergence; min-max problems; quadratic approximations; search direction; superlinearly convergent algorithm; Chebyshev approximation; Constraint optimization; Contracts; Convergence; Costs; Design engineering; Laboratories; Minimax techniques; Newton method; Quadratic programming;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location
Tampa, FL
Type
conf
DOI
10.1109/CDC.1989.70250
Filename
70250
Link To Document