Estimation of Distribution Immune Genetic Algorithm and Convergence Analysis - LIU Zhen; HU Yun-an; SHI Jian-guo (Indonesian Journal of Electrical Engineering and Computer Science, 2013)
In the traditional immune genetic algorithm, crossover and mutation can disrupt the superior chromosome, so make the algorithm took a long time to converge to the best solution. The way of crossover and mutation based on marginal product model which can make the algorithm converge quickly was proposed in order to avoid the disruption of the superior chromosome. The pseudo parallel evolution mechanism was also brought into the proposed algorithm in order to enhance the diversity of the population. The convergence character of the algorithm is analyzed. The model theorem of estimation of distribution immune genetic algorithm was given and the convergence rule was also given. Simulation results of several benchmark functions show that the proposed algorithm is superior than genetic algorithm immune genetic algorithm. So the proposed algorithm is correct and feasible. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1933