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Stopping criteria for a general model of genetic algorithm

Studniarski M.

Prace Naukowe Politechniki Warszawskiej. Elektronika

2009

z. 169

173-181

We consider a general Markov chain model of genetic algorithm described in [3], Chapters 5 and 6. For this model, we establish an upper bound for the number of iterations which must be executed in order to find an optimal (or approximately optimal) solution with a prescribed probability. For the classical genetic algorithm with bitwise mutation, our result reduces to the main theorem of [1] in the case of one optimal solution, and gives some improvement over it in the case of many optimal solutions.