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FOCS
1992
IEEE

Maximizing Non-Linear Concave Functions in Fixed Dimension

13 years 8 months ago
Maximizing Non-Linear Concave Functions in Fixed Dimension
Consider a convex set P in IRd and a piecewise polynomial concave function F: P IR. Let A be an algorithm that given a point x IRd computes F(x) if x P, or returns a concave polynomial p such that p(x) < 0 but for any y P, p(y) 0. We assume that d is fixed and that all comparisons in A depend on the sign of polynomial functions of the input point. We show that under these conditions, one can find maxP F in time which is polynomial in the number of arithmetic operations of A. Using our method we give the first strongly polynomial algorithms for many non-linear parametric problems in fixed dimension, such as the parametric max flow problem, the parametric minimum s-t distance, the parametric spanning tree problem and other problems. We also present an efficient algorithm for a very general convex programming problem in fixed dimension.
Sivan Toledo
Added 10 Aug 2010
Updated 10 Aug 2010
Type Conference
Year 1992
Where FOCS
Authors Sivan Toledo
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