Don’t Evaluate, Inherit

This paper studies fitness inheritance as an efficiency enhancement technique for genetic and evolutionary algorithms. Convergence and population sizing models are derived and compared with experimental results. These models are optimized for greatest speed-up and the optimal inheritance proportion to obtain such a speed-up is derived. Results also show that when the inheritance effects are considered in the population sizing model, the number of function evaluations are reduced by 20 % with the use of fitness inheritance. Results indicate that for a fixed population size, the number of function evaluations can be reduced by 70 % using a simple fitness inheritance technique.