Enhance Diversified Top-K MaxSAT Solving by Incorporating New Strategy for Generating Diversified Initial Assignments (Student Abstract)
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.
Cite
Text
Liang et al. "Enhance Diversified Top-K MaxSAT Solving by Incorporating New Strategy for Generating Diversified Initial Assignments (Student Abstract)." AAAI Conference on Artificial Intelligence, 2024. doi:10.1609/AAAI.V38I21.30473Markdown
[Liang et al. "Enhance Diversified Top-K MaxSAT Solving by Incorporating New Strategy for Generating Diversified Initial Assignments (Student Abstract)." AAAI Conference on Artificial Intelligence, 2024.](https://mlanthology.org/aaai/2024/liang2024aaai-enhance/) doi:10.1609/AAAI.V38I21.30473BibTeX
@inproceedings{liang2024aaai-enhance,
title = {{Enhance Diversified Top-K MaxSAT Solving by Incorporating New Strategy for Generating Diversified Initial Assignments (Student Abstract)}},
author = {Liang, Jiaxin and Zhou, Junping and Yin, Minghao},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2024},
pages = {23561-23562},
doi = {10.1609/AAAI.V38I21.30473},
url = {https://mlanthology.org/aaai/2024/liang2024aaai-enhance/}
}