A Lower Bound on CNF Encodings of the At-most-one Constraint

0494392 - ÚI 2020 RIV NL eng J - Článek v odborném periodiku
Kučera, P. - Savický, Petr - Vorel, V.
A Lower Bound on CNF Encodings of the At-most-one Constraint.
Theoretical Computer Science. Roč. 762, March (2019), s. 51-73. ISSN 0304-3975. E-ISSN 1879-2294
Grant CEP: GA ČR GBP202/12/G061
Grant ostatní: GA ČR(CZ) GA15-15511S
Institucionální podpora: RVO:67985807
Klíčová slova: Knowledge compilation * Cardinality constraint * At most one constraint * Propagation complete encoding
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 0.747, rok: 2019
Způsob publikování: Omezený přístup
http://dx.doi.org/10.1016/j.tcs.2018.09.003

Constraint 'at most one' is a basic cardinality constraint which requires that at most one of its n boolean inputs is set to 1. This constraint is widely used when translating a problem into a conjunctive normal form (CNF) and we investigate its CNF encodings suitable for this purpose. An encoding differs from a CNF representation of a function in that it can use auxiliary variables. We are especially interested in propagation complete encodings which have the property that unit propagation is strong enough to enforce consistency on input variables. We show a lower bound on the number of clauses in any propagation complete encoding of the 'at most one' constraint. The lower bound almost matches the size of the best known encodings. We also study an important case of 2-CNF encodings where we show a slightly better lower bound. The lower bound holds also for a related 'exactly one' constraint.
Trvalý link: http://hdl.handle.net/11104/0287600