AAAI 2024technical0 citations
Enhance Diversified Top-k MaxSAT Solving by Incorporating New Strategy for Generating Diversified Initial Assignments (Student Abstract)
Jiaxin Liang, Junping Zhou, Minghao Yin
Abstract
The Diversified Top-k MaxSAT (DTKMS) problem is an extension of MaxSAT. The objective of DTKMS is to find k feasible assignments of a given formula, such that each assignment satisfies all hard clauses and the k assignments together satisfy the maximum number of soft clauses. This paper presents a local search algorithm, DTKMS-DIA, which incorporates a new approach to generating initial assignments. Experimental results indicate that DTKMS-DIA can achieve attractive performance on 826 instances compared with state-of-the-art solvers.
BibTeX
@article{Liang_Zhou_Yin_2024, title={Enhance Diversified Top-k MaxSAT Solving by Incorporating New Strategy for Generating Diversified Initial Assignments (Student Abstract)}, volume={38}, url={https://ojs.aaai.org/index.php/AAAI/article/view/30473}, DOI={10.1609/aaai.v38i21.30473}, abstractNote={The Diversified Top-k MaxSAT (DTKMS) problem is an extension of MaxSAT. The objective of DTKMS is to find k feasible assignments of a given formula, such that each assignment satisfies all hard clauses and the k assignments together satisfy the maximum number of soft clauses. This paper presents a local search algorithm, DTKMS-DIA, which incorporates a new approach to generating initial assignments. Experimental results indicate that DTKMS-DIA can achieve attractive performance on 826 instances compared with state-of-the-art solvers.}, number={21}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Liang, Jiaxin and Zhou, Junping and Yin, Minghao}, year={2024}, month={Mar.}, pages={23561-23562} }