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)

Abstract

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
Pages52-59
DOIs
Publication statusPublished - 2013
Externally publishedYes

Cite this

Brys, T., Drugan, M. M., De Cock, M., Bosman, P. A. N., & Nowe, A. (2013). Local search and restart strategies for satisfiability solving in fuzzy logics. In 2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), 16-19 April 2013, Singapore (pp. 52-59). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/GEFS.2013.6601055