Indonesian Journal of Electrical Engineering and Computer Science
Vol 11, No 1: January 2013

Estimation of Distribution Immune Genetic Algorithm and Convergence Analysis

LIU Zhen (Naval Aeronautical and Astronautical University)
HU Yun-an (Naval Aeronautical and Astronautical University)
SHI Jian-guo (Naval Aeronautical and Astronautical University)



Article Info

Publish Date
10 Jan 2013

Abstract

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

Copyrights © 2013