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Combinatorial n-fold integer programming and applications

  • Dušan Knop
  • Martin Koutecký
  • Matthias MnichEmail author
Full Length Paper Series A
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Abstract

Many fundamental \(\mathsf {NP}\)-hard problems can be formulated as integer linear programs (ILPs). A famous algorithm by Lenstra solves ILPs in time that is exponential only in the dimension of the program, and polynomial in the size of the ILP. That algorithm became a ubiquitous tool in the design of fixed-parameter algorithms for \(\mathsf {NP}\)-hard problems, where one wishes to isolate the hardness of a problem by some parameter. However, in many cases using Lenstra’s algorithm has two drawbacks: First, the run time of the resulting algorithms is often double-exponential in the parameter, and second, an ILP formulation in small dimension cannot easily express problems involving many different costs. Inspired by the work of Hemmecke et al. (Math Program 137(1–2, Ser. A):325–341, 2013), we develop a single-exponential algorithm for so-called combinatorialn-fold integer programs, which are remarkably similar to prior ILP formulations for various problems, but unlike them, also allow variable dimension. We then apply our algorithm to many relevant problems problems like Closest String, Swap Bribery, Weighted Set Multicover, and several others, and obtain exponential speedups in the dependence on the respective parameters, the input size, or both. Unlike Lenstra’s algorithm, which is essentially a bounded search tree algorithm, our result uses the technique of augmenting steps. At its heart is a deep result stating that in combinatorial n-fold IPs, existence of an augmenting step implies existence of a “local” augmenting step, which can be found using dynamic programming. Our results provide an important insight into many problems by showing that they exhibit this phenomenon, and highlights the importance of augmentation techniques.

Keywords

Integer programming Augmentation algorithm Closest string Fixed-parameter algorithms 

Mathematics Subject Classification

90C10 90C27 90C39 

Notes

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society 2019

Authors and Affiliations

  1. 1.Department of Theoretical Computer Science, Faculty of Information TechnologyCzech Technical University in PraguePragueCzech Republic
  2. 2.Technion - Israel Institute of TechnologyHaifaIsrael
  3. 3.Charles UniversityPragueCzech Republic
  4. 4.TU Hamburg, Institute for Algorithms and ComplexityHamburgGermany
  5. 5.Universität BonnBonnGermany

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