Abstract
In this paper we present DeMaxSAT, a memetic algorithm for solving the non-partial MaxSAT problem. It combines the evolutionary algorithm of Differential Evolution with GSAT and RandomWalk, two MaxSAT-specific local search heuristics. An implementation of the algorithm has been used to solve the benchmarks for non-partial MaxSAT included in the MaxSAT Evaluation 2021. The performance of DeMaxSAT has reached results that are comparable, both in computing time and quality of the solutions, to the best solvers presented in MaxSAT Evaluation 2021, reaching the state of the art for non-partial problems.
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Notes
- 1.
The code of DeMaxSAT is available at [1].
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Acknowledgments
Partially funded by the Xunta de Galicia and the European Union (European Regional Development Fund - Galicia 2014–2020 Program), with grants CITIC (ED431G 2019/01) and GPC ED431B 2022/33, and by the Spanish Ministry of Science and Innovation (grant PID2020-116201GB-I00).
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Framil, M., Cabalar, P., Santos, J. (2022). A MaxSAT Solver Based on Differential Evolution (Preliminary Report). In: Marreiros, G., Martins, B., Paiva, A., Ribeiro, B., Sardinha, A. (eds) Progress in Artificial Intelligence. EPIA 2022. Lecture Notes in Computer Science(), vol 13566. Springer, Cham. https://doi.org/10.1007/978-3-031-16474-3_55
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