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Convex integer maximization via Graver bases. (English) Zbl 1284.05026
Summary: We present a new algebraic algorithmic scheme to solve convex integer maximization problems of the following form, where $$c$$ is a convex function on $$\mathbb R^d$$ and $$w_{1}x,\dots ,w_dx$$ are linear forms on $$\mathbb R^n$$, $\max\{c(w_1x,\dots , w_dx): Ax = b, x \in \mathbb N^n\}.$ This method works for arbitrary input data $$A,b,d,w_{1},\dots ,w_{d},c$$. Moreover, for fixed $$d$$ and several important classes of programs in variable dimension, we prove that our algorithm runs in polynomial time. As a consequence, we obtain polynomial time algorithms for various types of multi-way transportation problems, packing problems, and partitioning problems in variable dimension.

##### MSC:
 05A17 Combinatorial aspects of partitions of integers 68Q17 Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.)
4ti2
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