Applying an Evolutionary Algorithm Inspired by Evolution of Birdsong Grammars to Variants of Large-scaled OneMax Problems

Abstract

We previously proposed the evolutionary algorithm inspired by the evolution of birdsong grammars. One of the objectives for the proposal was to quickly obtain practical solutions to large-scaled problems. However, we did not apply the algorithm to large-scaled problems there. So, in the paper, we apply the algorithm to a large-scaled OneMax problem and its variants. The simulation results show that the algorithm is likely to produce solutions with simple bit patters and with not so bad fitness values for large-scaled problems as a bit pattern of the global optimum becomes more random. However, when the problem size is smaller, the algorithm is likely to produce a precise bit pattern of the global optimum.