Arrow Research search
Back to AAAI

AAAI 2014

Tailoring Local Search for Partial MaxSAT

Conference Paper Papers Artificial Intelligence

Abstract

Partial MaxSAT (PMS) is a generalization to SAT and MaxSAT. Many real world problems can be encoded into PMS in a more natural and compact way than SAT and MaxSAT. In this paper, we propose new ideas for local search for PMS, which mainly rely on the distinction between hard and soft clauses. We use these ideas to develop a local search PMS algorithm called Dist. Experimental results on PMS benchmarks from MaxSAT Evaluation 2013 show that Dist significantly outperforms state-of-the-art PMS algorithms, including both local search algorithms and complete ones, on random and crafted benchmarks. For the industrial benchmark, Dist dramatically outperforms previous local search algorithms and is comparable with complete algorithms.

Authors

Keywords

No keywords are indexed for this paper.

Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
989087407477633136
v2026.09.13