An Evolutionary Local Search Algorithm for the Satisfiability Problem

Satisfiability problem is an NP-complete problem that finds itself or its variants in many combinatorial problems. There exist many complete algorithms that give successful results on hard problems, but they may be time-consuming because of their branch and bound structures. In this manner, many suc...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Aksoy, Levent, Gunes, Ece Olcay
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Satisfiability problem is an NP-complete problem that finds itself or its variants in many combinatorial problems. There exist many complete algorithms that give successful results on hard problems, but they may be time-consuming because of their branch and bound structures. In this manner, many successful incomplete algorithms are introduced. In this paper, the improvement of incomplete algorithms is of interest and it is shown that the incomplete algorithms can be more efficient if they are equipped with the problem specific knowledge, goal-oriented operators, and knowledge-based methods. In this aspect, an evolutionary local search algorithm is implemented, tested on a randomly generated benchmark that includes test instances with different sizes, and compared with prominent incomplete algorithms. Also, effects of goal-oriented genetic operators and knowledge-based methods used in the evolution-ary local search algorithm are examined by making comparisons with blind operators and random methods.
ISSN:0302-9743
1611-3349
DOI:10.1007/11803089_22