A Structural Approach to Kernels for ILPs: Treewidth and Total Unimodularity
A Structural Approach to Kernels for ILPs: Treewidth and Total Unimodularity
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ILP 内核的结构方法:树宽和总单模性
DOI:
10.1007/978-3-662-48350-3_65
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发表时间:
2015
期刊:
影响因子:
--
通讯作者:
Stefan Kratsch
中科院分区:
文献类型:
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作者:
Bart M. P. Jansen;Stefan Kratsch
Kernelization is a theoretical formalization of efficient preprocessing forNP-hard problems. Empirically, preprocessing is highly successful in practice, for example in state-of-the-art ILP-solvers like CPLEX. Motivated by this, previous work studied the existence of kernelizations for ILP related problems, e.g., for testing feasibility ofAx≤b. In contrast to the observed success of CPLEX, however, the results were largely negative. Intuitively, practical instances have far more useful structure than the worst-case instances used to prove these lower bounds.In the present paper, we study the effect that subsystems that have (a Gaifman graph of) bounded treewidth or that are totally unimodular have on the kernelizability of the ILP feasibility problem. We show that, on the positive side, if these subsystems have a small number of variables on which they interact with the remaining instance, then we can efficiently replace them by smaller subsystems of size polynomial in the domain without changing feasibility. Thus, if large parts of an instance consist of such subsystems, then this yields a substantial size reduction. Complementing this we prove that relaxations to the considered structures, e.g., larger boundaries of the subsystems, allow worst-case lower bounds against kernelization. Thus, these relaxed structures give rise to instance families that cannot be efficiently reduced, by any approach.
DOI:
10.1007/978-3-642-40450-4_55
发表时间:
2013
期刊:
影响因子:
--
作者:
Stefan Kratsch
通讯作者:
Stefan Kratsch
DOI:
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发表时间:
2013
期刊:
Journal of computer and system sciences (Print)
影响因子:
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作者:
Stefan Kratsch
通讯作者:
Stefan Kratsch
DOI:
10.1145/2797140
发表时间:
2012-07
期刊:
ACM Transactions on Algorithms (TALG)
影响因子:
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作者:
Eun Jung Kim;Alexander Langer;C. Paul;F. Reidl;P. Rossmanith;Ignasi Sau;S. Sikdar
通讯作者:
Eun Jung Kim;Alexander Langer;C. Paul;F. Reidl;P. Rossmanith;Ignasi Sau;S. Sikdar