Generalized net models of basic genetic algorithm operators
© Springer International Publishing Switzerland 2016. Generalized nets (GN) are applied here to describe some basic operators of genetic algorithms, namely selection, crossover and mutation and different functions for selection (roulette wheel selection method and stochastic universal sampling), different crossover techniques (one-point crossover, two-point crossover, and “cut and splice” technique), as well as mutation operator (mutation operator of the Breeder genetic algorithm). The resulting GN models can be considered as separate modules, but they can also be accumulated into a single GN model to describe a whole genetic algorithm.
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