This paper proposes a genetic sequential IB algorithm.It takes several seeding solutions of the basic sequential IB algorithm as initial population

and then integrates this population into a solution using the integration operator.Sequentially

some certain positions of the obtained solution are selected and mutated iteratively based on the defined instability statistic.After mutation of several generations

the iterative process terminates and a more optimal solution is obtained.Experimental results on the benchmark data sets indicate that the proposed algorithm outperforms the sequential IB algorithm in both the accuracy and the efficiency.