A New Hybrid Evolutionary Algorithm Based on ICA and GA: Recursive-ICA-GA

In this paper a new method is proposed based on the combination of ICA (Imperial Competitive Algorithm) and GA (Genetic Algorithm) which improves the convergence speed and accuracy of the optimization results. The new algorithm, which is named R-ICA-GA (RecursiveICA-GA), runs ICA and GA consecutively. It is shown that a fast decrease occurs while the proposed algorithm switches from ICA to GA. The main goal of the new proposed algorithm is to achieve a faster optimization technique by applying this fast decrease. Moreover, the simple combination of ICA and GA, which is named ICA-GA, is presented in this study. These two combination schemes of ICA and GA are used for comparing with other conventional algorithms. Finally, three fitness functions are used for comparing the suggested algorithms. The obtained results show that compared with the previous method, the proposed algorithms are at least 32% faster in optimization processes; also the variance convergence speed is smaller than the ICA and GA.