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FPTAS for optimizing polynomials over the mixed-integer points of polytopes in fixed dimension
Authors:Jesús A De Loera  Raymond Hemmecke  Matthias Köppe  Robert Weismantel
Institution:1. Department of Mathematics, University of California, Davis, CA, 95616, USA
2. Otto-von-Guericke-Universit?t Magdeburg, FMA/IMO, Universit?tsplatz 2, 39106, Magdeburg, Germany
Abstract:We show the existence of a fully polynomial-time approximation scheme (FPTAS) for the problem of maximizing a non-negative polynomial over mixed-integer sets in convex polytopes, when the number of variables is fixed. Moreover, using a weaker notion of approximation, we show the existence of a fully polynomial-time approximation scheme for the problem of maximizing or minimizing an arbitrary polynomial over mixed-integer sets in convex polytopes, when the number of variables is fixed. A conference version of this article, containing a part of the results presented here, appeared in Proceedings of the 17th Annual ACM-SIAM Symposium on Discrete Algorithms, Miami, FL, January 22–24, 2006, pp. 743–748. The first author gratefully acknowledges support from NSF grant DMS-0608785, a 2003 UC-Davis Chancellor’s fellow award, the Alexander von Humboldt foundation, and IMO Magdeburg. The remaining authors were supported by the European TMR network ADONET 504438.
Keywords:Mixed-integer nonlinear programming  Integer programming in fixed dimension  Computational complexity  Approximation algorithms  FPTAS
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