Christoph Hunkenschröder, Kim-Manuel Klein, Martin Koutecký, Alexandra Lassota, Asaf Levin
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引用次数: 0
Abstract
We study fundamental block-structured integer programs called tree-fold and multi-stage IPs. Tree-fold IPs have a constraint matrix with independent blocks linked together by few constraints in a recursive pattern. Transposing this constraint matrix yields the constraint matrix of multi-stage IPs. The state-of-the-art algorithms to solve these IPs have an exponential gap in their running times, making it natural to ask whether this gap is inherent. We answer this question in the affirmative. Assuming the Exponential Time Hypothesis, we prove lower bounds showing that the exponential difference is necessary. This also proves that the known algorithms are essentially optimal. Moreover, we prove unconditional lower bounds on the size of the Graver basis elements, a fundamental building block of all known algorithms to solve these IPs. This shows that none of the current approaches can be improved beyond this bound unconditionally.
期刊介绍:
Mathematical Programming publishes original articles dealing with every aspect of mathematical optimization; that is, everything of direct or indirect use concerning the problem of optimizing a function of many variables, often subject to a set of constraints. This involves theoretical and computational issues as well as application studies. Included, along with the standard topics of linear, nonlinear, integer, conic, stochastic and combinatorial optimization, are techniques for formulating and applying mathematical programming models, convex, nonsmooth and variational analysis, the theory of polyhedra, variational inequalities, and control and game theory viewed from the perspective of mathematical programming.