Analysis of crossover rate in variable size Genetic Network Programming with binomial distribution

Variable Size Genetic Network Programming (GNPvs) with Binomial Distribution is a new type of Genetic Network Programming, which permits the individuals with variable size and obtains the optimal size of individuals during evolution. In contrast to swapping the corresponding nodes in the crossover of Genetic Network Programming (GNP), the crossover of GNPvs moves a number of nodes from each parent individual to another parent individual. The probability of selecting the number of nodes to move satisfies the binomial distribution, which is controls by the crossover rate and the initial size of the individuals. In this paper, the performance of the algorithm and the size of the individuals are studied by changing the most important parameter, i.e., crossover rate. Since GNPvs may suffer from the bloating problem, the Island Model is introduced to control the size of the individuals implicitly. The well-known test bed Tileworld is used to show the numeric results in the simulations.