Finding all minimal elements of a finite partially ordered set by genetic algorithm with a prescribed probability
Marcin Studniarski
Numerical Algebra, Control & Optimization 2011, 1(3): 389-398 doi: 10.3934/naco.2011.1.389
For a general Markov chain model of genetic algorithm, we establish an upper bound for the number of iterations which must be executed in order to find, with a prescribed probability, an optimal solution in a finite multiobjective optimization problem.
keywords: stopping criteria. vector optimization Genetic algorithm Markov chain

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