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(mn2L+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>n2
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 :
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