DocumentCode
2178591
Title
A new algorithm for minimizing convex functions over convex sets
Author
Vaidya, Pravin M.
Author_Institution
AT&T Bell Labs., Murray Hill, NJ, USA
fYear
1989
fDate
30 Oct-1 Nov 1989
Firstpage
338
Lastpage
343
Abstract
An algorithm for minimizing a convex function over a convex set is given. The notion of a volumetric center of a polytope and a related ellipsoid of maximum volume inscribable in the polytope is central to the algorithm. The algorithm has a much better rate of global convergence than the ellipsoid algorithm. A by-product of the algorithm is an algorithm for solving linear programming problems that performs a total of O (mn 2L +M (n )nL ) arithmetic operations in the worst case, where m is the number of constraints, n the number of variables, and L a certain parameter. This gives an improvement in the time complexity of linear programming for m >n 2
Keywords
computational complexity; linear programming; convex functions; global convergence; linear programming; polytope; related ellipsoid; time complexity; volumetric center; Computational efficiency; Convergence; Ellipsoids; Iterative algorithms; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Foundations of Computer Science, 1989., 30th Annual Symposium on
Conference_Location
Research Triangle Park, NC
Print_ISBN
0-8186-1982-1
Type
conf
DOI
10.1109/SFCS.1989.63500
Filename
63500
Link To Document