A parallel genetic algorithm with adaptive adjustment of genetic parameters

This paper proposes a new parallel genetic algorithm with adaptive adjustment of genetic parameters, which runs on a hierarchical island model. During the execution of the parallel GA, each subpopulation executes an adaptive GA, and genetic parameters of a subpopulation with low performance are adaptively adjusted by exchanging the values of genetic parameters among the neighboring subpopulations. Experimental results show the effectiveness of the proposed algorithm compared to a parallel genetic algorithm without adaptive parameter adjustment among subpopulations.

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