2017
Solving Integer Linear Programs with a Small Number of Global Variables and Constraints
DVORAK, Pavel, Eduard EIBEN, Robert GANIAN, Dusan KNOP, Sebastian ORDYNIAK et. al.Základní údaje
Originální název
Solving Integer Linear Programs with a Small Number of Global Variables and Constraints
Autoři
DVORAK, Pavel (203 Česká republika), Eduard EIBEN (703 Slovensko), Robert GANIAN (203 Česká republika, garant, domácí), Dusan KNOP (203 Česká republika) a Sebastian ORDYNIAK (40 Rakousko)
Vydání
USA, Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, {IJCAI} 2017, Melbourne, Australia, August 19-25, 2017, od s. 607-613, 7 s. 2017
Nakladatel
ijcai.org
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10200 1.2 Computer and information sciences
Stát vydavatele
Spojené státy
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
elektronická verze "online"
Odkazy
Kód RIV
RIV/00216224:14330/17:00100548
Organizační jednotka
Fakulta informatiky
ISBN
978-0-9992411-0-3
ISSN
UT WoS
000764137500085
Klíčová slova anglicky
Integer Linear Programming; Backdoors; Parameterized Algorithms
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 16. 5. 2022 15:49, Mgr. Michal Petr
Anotace
V originále
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. Our main contributions can be divided into three parts. First, we formally develop fracture backdoors and obtain exact and approximation algorithms for computing these. Second, we exploit these backdoors to develop several new parameterized algorithms for ILP; the performance of these algorithms will naturally scale based on the number of global variables or constraints in the instance. Finally, we complement the developed algorithms with matching lower bounds. Altogether, our results paint a near-complete complexity landscape of ILP with respect to fracture backdoors.