Genetic drift in evolutionary computation, which results from the selection pressure, sampling error and recombination, drives the population to converge to a single individual uniformly, thus causing premature stagnation or losing alternative global or local optima. For multi-parent diagonal crossover and scanning crossover are generalizations of the various conventional crossover and recombination operators, genetic drift from which is analyzed theoretically in this paper. By analyzing the frequency of the dominant allele, it is strictly proved that multi-parent diagonal crossover and uniform scanning crossover do not cause a genetic drift, but multi-parent occurrence-based scanning crossover induces a strong genetic drift that augments with the increasing of the number of parents. The simulant genetic optimization shows that the genetic drift induced by multi-parent occurrence-based scanning crossover reduces both the population diversity and the convergence rate, thus deteriorating the performance of an evolutionary search.