Local search and restart strategies for satisfiability solving in fuzzy logics

T. Brys, M.M. Drugan, M. De Cock, P.A.N. Bosman, A. Nowe

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)


Satisfiability solving in fuzzy logics is a subject that has not been researched much, certainly compared to satisfiability in propositional logics. Yet, fuzzy logics are a powerful tool for modelling complex problems. Recently, we proposed an optimization approach to solving satisfiability in fuzzy logics and compared the standard Covariance Matrix Adaptation Evolution Strategy algorithm (CMA-ES) with an analytical solver on a set of benchmark problems. Especially on more finegrained problems did CMA-ES compare favourably to the analytical approach. In this paper, we evaluate two types of hillclimber in addition to CMA-ES, as well as restart strategies for these algorithms. Our results show that a population-based hillclimber outperforms CMA-ES on the harder problem class.
Original languageEnglish
Title of host publication2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), 16-19 April 2013, Singapore
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Publication statusPublished - 2013
Externally publishedYes


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