By Topic

Towards a Generic CNF Simplifier for Minimising Structured Problem Hardness

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Anbulagan ; NICTA, Australian Nat. Univ., Canberra, ACT, Australia ; John Slaney

CNF simplifiers play a very important role in minimising structured problem hardness. Although they can be used in an in-search process, most of them serve in a pre-search phase and rely on one form or another of resolution. Based on our understanding about problem structure, in the paper, we extend the single pre-search process to a multiple one in order to further simplify the hard structure in a problem. This extension boosts the performance of state-of-the-art clause learning and lookahead based SAT solvers when solving both satisfiable and unsatisfiable instances of many real-world hard combinatorial problems.

Published in:

2009 21st IEEE International Conference on Tools with Artificial Intelligence

Date of Conference:

2-4 Nov. 2009