Distributed segregative genetic algorithm for solving fuzzy equations

Authors:
Octav Brudaru;Octavian Buzatu
Affiliations:
Department of System Engineering and Management, Technical University "Gh. Asachi", Iasi, Romania and Institute of Computer Science, Romanian Academy, Iasi, Romania;Institute of Computer Science, Romanian Academy, Iasi, Romania
Venue:
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Year:
2007

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Abstract

This paper presents a genetic algorithm for solving fuzzy equations that evolves many sub-populations of solutions. The individuals are clustered into groups using a features based similarity measure. A distributed implementation of this segregative GA containing a communication mechanism that enforces the clustering structure of the subpopulations is described. The results of the experimental investigation of the ability to find multiple accurate roots as well as the effect of alternative distributed models and communication schemes are reported.