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- W4312141303 abstract "The (weighted) partial maximum satisfiability ((W)PMS) problem is an important generalization of the classic problem of propositional (Boolean) satisfiability with a wide range of real-world applications. In this paper, we propose an initialization and a diversification strategy to improve local search for the (W)PMS problem. Our initialization strategy is based on a novel definition of variables' structural entropy, and it aims to generate a solution that is close to a high-quality feasible one. Then, our diversification strategy picks a variable in two possible ways, depending on a parameter: continuing to pick variables with the best benefits or focusing on a clause with the greatest penalty and then selecting variables probabilistically. Based on these strategies, we developed a local search solver dubbed ImSATLike, as well as a hybrid solver ImSATLike-TT, and experimental results on (weighted) partial MaxSAT instances in recent MaxSAT Evaluations show that they outperform or have nearly the same performances as state-of-the-art local search and hybrid competitors, respectively, in general. Furthermore, we carried out experiments to confirm the individual impacts of each proposed strategy." @default.
- W4312141303 created "2023-01-04" @default.
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- W4312141303 date "2022-12-18" @default.
- W4312141303 modified "2023-10-15" @default.
- W4312141303 title "Initial Solution Generation and Diversified Variable Picking in Local Search for (Weighted) Partial MaxSAT" @default.
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- W4312141303 doi "https://doi.org/10.3390/e24121846" @default.
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