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The complexity landscape of decompositional parameters for ILP: Programs with few global variables and constraints

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F21%3A00351631" target="_blank" >RIV/68407700:21240/21:00351631 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.artint.2021.103561" target="_blank" >https://doi.org/10.1016/j.artint.2021.103561</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.artint.2021.103561" target="_blank" >10.1016/j.artint.2021.103561</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    The complexity landscape of decompositional parameters for ILP: Programs with few global variables and constraints

  • Original language description

    Integer Linear Programming (ILP) has a broad range of applications in various areas of artificial intelligence. Yet in spite of recent advances, we still lack a thorough understanding of which structural restrictions make ILP tractable. Here we study ILP instances consisting of a small number of "global" variables and/or constraints such that the remaining part of the instance consists of small and otherwise independent components; this is captured in terms of a structural measure we call fracture backdoors which generalizes, for instance, the well-studied class of N-fold ILP instances.

  • Czech name

    —

  • Czech description

    —

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

    —

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    —

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2021

  • 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

    1872-7921

  • Volume of the periodical

    300

  • Issue of the periodical within the volume

    103561

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    21

  • Pages from-to

    —

  • UT code for WoS article

    000697026000011

  • EID of the result in the Scopus database

    2-s2.0-85111647226