Solving MAXSAT by Solving a Sequence of Simpler SAT Instances

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MLIC: A MaxSAT-Based Framework for Learning Interpretable Classification Rules (2018, methodology): “We also experimented with LMHS [3], another state of the art MaxSAT solver and MaxHS outperformed LMHS for our benchmarks 6.”
Techniques Inspired by Local Search for Incomplete MaxSAT and the Linear Algorithm: Varying Resolution and Solution-Guided Search (2019, methodology): “Hitting-set approaches [9, 23] utilise unsatisﬁable cores to separate MaxSAT solving into a SAT and an integer programming component.”
Iterative and core-guided MaxSAT solving: A survey and assessment (2013, methodology): “Such approaches include an algorithm [40] that uses linear programming technology to handle the cardinality and pseudoBoolean constraints, more aggressive computation of lower bounds and upper bounds at each disjoint core for the core-guided binary search with disjoint cores algorithm [92], and the ”
Improving the Effectiveness of SAT-Based Preprocessing for MaxSAT (2015, methodology): “In this work we lift the previously proposed MaxHS [Davies and Bacchus, 2011; 2013a; 2013b] algorithm into the LCNF framework.”