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Tight Complexity Lower Bounds for Integer Linear Programming with Few Constraints

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00342828" target="_blank" >RIV/68407700:21240/20:00342828 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1145/3397484" target="_blank" >https://doi.org/10.1145/3397484</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3397484" target="_blank" >10.1145/3397484</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Tight Complexity Lower Bounds for Integer Linear Programming with Few Constraints

  • Original language description

    We consider the standard ILP Feasibility problem: given an integer linear program of the form {Ax = b, x >= 0}, where A is an integer matrix with k rows and ℓ columns, x is a vector of ℓ variables, and b is a vector of k integers, we ask whether there exists x element N ℓ that satisfies Ax = b. Each row of A specifies one linear constraint on x; our goal is to study the complexity of ILP Feasibility when both k, the number of constraints, and Ainfinity, the largest absolute value of an entry in A, are small. Papadimitriou was the first to give a fixed-parameter algorithm for ILP Feasibility under parameterization by the number of constraints that runs in time ((Ainfinity + binfinity) ⋅ k)O(k2). This was very recently improved by Eisenbrand and Weismantel, who used the Steinitz lemma to design an algorithm with running time (kAinfinity)O(k) ⋅ log binfinity, which was subsequently refined by Jansen and Rohwedder to O( kAinfinity)k ⋅ log ( Ainfinity + binfinity) ⋅ log Ainfinity. We prove that for {0, 1}-matrices A, the running time of the algorithm of Eisenbrand and Weismantel is probably optimal: an algorithm with running time 2o(k log k) ⋅ (ℓ + binfinity)o(k) would contradict the exponential time hypothesis. This improves previous non-tight lower bounds of Fomin et al. We then consider integer linear programs that may have many constraints, but they need to be structured in a "shallow" way. Precisely, we consider the parameter dual treedepth of the matrix A, denoted tdD(A), which is the treedepth of the graph over the rows of A, where two rows are adjacent if in some column they simultaneously contain a non-zero entry. It was recently shown by Koutecký et al. that ILP Feasibility can be solved in time Ainfinity2O(tdD(A)) ⋅ (k + ℓ + log binfinity)O(1). We present a streamlined proof of this fact and prove that, again, this running time is probably optimal: even assuming that all entries of A and b are in {-1, 0, 1}, the existence of an algorithm with running time 22o(tdD(A)) ⋅ (k + ℓ)O(1) would contradict the exponential time hypothesis.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS 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

    <a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    ACM Transactions on Computation Theory

  • ISSN

    1942-3454

  • e-ISSN

    1942-3462

  • Volume of the periodical

    12

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    19

  • Pages from-to

    "19:1"-"19:19"

  • UT code for WoS article

    000583677700005

  • EID of the result in the Scopus database

    2-s2.0-85088097305