Eunice E. Santos, Lehigh University, USA; Eugene Santos Jr., University of Connecticut, USA
Fitness function computations are a bottleneck in genetic algorithms (GAs). Caching of partial results from these fitness computations can reduce this bottleneck. We provide a rigorous analysis of the run-times of GAs with and without caching. By representing fitness functions as classic Divide and Conquer algorithms, we provide a formal model to predict the efficiency of caching GAs vs. non-caching GAs. Finally, we explore the domain of protein folding with GAs and demonstrate that caching can significantly reduce expected run-times.