Standard

Solving Boolean satisfiability using local search guided by unit clause elimination. / Hirsch, Edward A.; Kojevnikov, Arist.

Principles and Practice of Constraint Programming - CP 2001 - 7th International Conference, CP 2001, Proceedings. ed. / Toby Walsh. Springer Nature, 2001. p. 605-609 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2239).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Hirsch, EA & Kojevnikov, A 2001, Solving Boolean satisfiability using local search guided by unit clause elimination. in T Walsh (ed.), Principles and Practice of Constraint Programming - CP 2001 - 7th International Conference, CP 2001, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2239, Springer Nature, pp. 605-609, 7th International Conference on Principles and Practice of Constraint Programming, CP 2001, Paphos, Cyprus, 26/11/01.

APA

Hirsch, E. A., & Kojevnikov, A. (2001). Solving Boolean satisfiability using local search guided by unit clause elimination. In T. Walsh (Ed.), Principles and Practice of Constraint Programming - CP 2001 - 7th International Conference, CP 2001, Proceedings (pp. 605-609). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2239). Springer Nature.

Vancouver

Hirsch EA, Kojevnikov A. Solving Boolean satisfiability using local search guided by unit clause elimination. In Walsh T, editor, Principles and Practice of Constraint Programming - CP 2001 - 7th International Conference, CP 2001, Proceedings. Springer Nature. 2001. p. 605-609. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Author

Hirsch, Edward A. ; Kojevnikov, Arist. / Solving Boolean satisfiability using local search guided by unit clause elimination. Principles and Practice of Constraint Programming - CP 2001 - 7th International Conference, CP 2001, Proceedings. editor / Toby Walsh. Springer Nature, 2001. pp. 605-609 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{4a96825086bc4f9d9085be8f26289425,
title = "Solving Boolean satisfiability using local search guided by unit clause elimination",
abstract = "In this paper we present a new randomized algorithm for SAT combining unit clause elimination and local search. The algorithm is inspired by two randomized algorithms having the best current worst-case upper bounds ([9] and [11,12]). Despite its simplicity, our algorithm performs well on many common benchmarks (we present results of its empirical evaluation). It is also probabilistically approximately complete.",
keywords = "Boolean satisfiability, Empirical evaluation, Local search",
author = "Hirsch, {Edward A.} and Arist Kojevnikov",
year = "2001",
month = jan,
day = "1",
language = "English",
isbn = "3540428631",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "605--609",
editor = "Toby Walsh",
booktitle = "Principles and Practice of Constraint Programming - CP 2001 - 7th International Conference, CP 2001, Proceedings",
address = "Germany",
note = "7th International Conference on Principles and Practice of Constraint Programming, CP 2001 ; Conference date: 26-11-2001 Through 01-12-2001",

}

RIS

TY - GEN

T1 - Solving Boolean satisfiability using local search guided by unit clause elimination

AU - Hirsch, Edward A.

AU - Kojevnikov, Arist

PY - 2001/1/1

Y1 - 2001/1/1

N2 - In this paper we present a new randomized algorithm for SAT combining unit clause elimination and local search. The algorithm is inspired by two randomized algorithms having the best current worst-case upper bounds ([9] and [11,12]). Despite its simplicity, our algorithm performs well on many common benchmarks (we present results of its empirical evaluation). It is also probabilistically approximately complete.

AB - In this paper we present a new randomized algorithm for SAT combining unit clause elimination and local search. The algorithm is inspired by two randomized algorithms having the best current worst-case upper bounds ([9] and [11,12]). Despite its simplicity, our algorithm performs well on many common benchmarks (we present results of its empirical evaluation). It is also probabilistically approximately complete.

KW - Boolean satisfiability

KW - Empirical evaluation

KW - Local search

UR - http://www.scopus.com/inward/record.url?scp=84947909669&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84947909669

SN - 3540428631

SN - 9783540428633

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 605

EP - 609

BT - Principles and Practice of Constraint Programming - CP 2001 - 7th International Conference, CP 2001, Proceedings

A2 - Walsh, Toby

PB - Springer Nature

T2 - 7th International Conference on Principles and Practice of Constraint Programming, CP 2001

Y2 - 26 November 2001 through 1 December 2001

ER -

ID: 49829404