A New Model of Parallel Distributed Genetic Algorithms for Cluster Systems: Dual Individual DGAs

Authors:
Tomoyuki Hiroyasu;Mitsunori Miki;Masahiro Hamasaki;Yusuke Tanimura
Affiliations:
-;-;-;-
Venue:
ISHPC '00 Proceedings of the Third International Symposium on High Performance Computing
Year:
2000

Citing 6
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Abstract

A new model of parallel distributed genetic algorithm, Dual Individual Distributed Genetic Algorithm (DuDGA), is proposed. This algorithm frees the user from having to set some parameters because each island of Distributed Genetic Algorithm (DGA) has only two individuals. DuDGA can automatically determine crossover rate, migration rate, and island number. Moreover, compared to simple GA and DGA methods, DuDGA can find better solutions with fewer analyses. Capability and effectiveness of the DuDGA method are discussed using four typical numerical test functions.