The complexity landscape of decompositional parameters for ILP
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00106822" target="_blank" >RIV/00216224:14330/18:00106822 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.artint.2017.12.006" target="_blank" >http://dx.doi.org/10.1016/j.artint.2017.12.006</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.artint.2017.12.006" target="_blank" >10.1016/j.artint.2017.12.006</a>
Alternative languages
Result language
angličtina
Original language name
The complexity landscape of decompositional parameters for ILP
Original language description
Integer Linear Programming (ILP) can be seen as the archetypical problem for NP-complete optimization problems, and a wide range of problems in artificial intelligence are solved in practice via a translation to ILP. Despite its huge range of applications, only few tractable fragments of ILP are known, probably the most prominent of which is based on the notion of total unimodularity. Using entirely different techniques, we identify new tractable fragments of ILP by studying structural parameterizations of the constraint matrix within the framework of parameterized complexity. In particular, we show that ILP is fixed-parameter tractable when parameterized by the treedepth of the constraint matrix and the maximum absolute value of any coefficient occurring in the ILP instance. Together with matching hardness results for the more general parameter treewidth, we give an overview of the complexity of ILP w.r.t. decompositional parameters defined on the constraint matrix.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ARTIFICIAL INTELLIGENCE
ISSN
0004-3702
e-ISSN
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Volume of the periodical
257
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
61-71
UT code for WoS article
000427335000003
EID of the result in the Scopus database
2-s2.0-85043375699