A novel genetic programming approach to control bloat using crossover and mutation with intelligence technique

Bloat is a problem that occurs when there is no advancement in fitness measure, but the size of the tree grows exponentially. Bloat eventually increases the time required to reach the optimal solution. To overcome this defect, Crossover and Mutation with Intelligence technique is proposed. We also used double tournament, in which we apply two tournaments on the basis of size and fitness respectively to select the individuals to perform Crossover with Intelligence. Our approach of overcoming bloat is tested experimentally on some benchmark datasets picked up from UCI repository and by some observations. The results verified that our Crossover and Mutation with Intelligence degrades the bloat phenomena.