AIDec 5, 2025

Enhancing Local Search for MaxSAT with Deep Differentiation Clause Weighting

arXiv:2512.05619v1Has Code
Originality Incremental advance
AI Analysis

This work addresses a specific bottleneck in MaxSAT solving for applications requiring efficient optimization, though it appears incremental in nature.

The authors tackled the problem of distinguishing between Partial Maximum Satisfiability (PMS) and Weighted Partial Maximum Satisfiability (WPMS) in Stochastic Local Search algorithms by developing a novel clause weighting scheme with distinct update conditions and initialization methods, resulting in a new solver DeepDist that outperforms state-of-the-art SLS solvers and, when hybridized, surpasses the MaxSAT Evaluation 2024 winners.

Partial Maximum Satisfiability (PMS) and Weighted Partial Maximum Satisfiability (WPMS) generalize Maximum Satisfiability (MaxSAT), with broad real-world applications. Recent advances in Stochastic Local Search (SLS) algorithms for solving (W)PMS have mainly focused on designing clause weighting schemes. However, existing methods often fail to adequately distinguish between PMS and WPMS, typically employing uniform update strategies for clause weights and overlooking critical structural differences between the two problem types. In this work, we present a novel clause weighting scheme that, for the first time, updates the clause weights of PMS and WPMS instances according to distinct conditions. This scheme also introduces a new initialization method, which better accommodates the unique characteristics of both instance types. Furthermore, we propose a decimation method that prioritizes satisfying unit and hard clauses, effectively complementing our proposed clause weighting scheme. Building on these methods, we develop a new SLS solver for (W)PMS named DeepDist. Experimental results on benchmarks from the anytime tracks of recent MaxSAT Evaluations show that DeepDist outperforms state-of-the-art SLS solvers. Notably, a hybrid solver combining DeepDist with TT-Open-WBO-Inc surpasses the performance of the MaxSAT Evaluation 2024 winners, SPB-MaxSAT-c-Band and SPB-MaxSAT-c-FPS, highlighting the effectiveness of our approach. The code is available at https://github.com/jmhmaxsat/DeepDist

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes