Genetic Programming for Julia: fast performance and parallel island model implementation

I introduce a Julia implementation for genetic programming (GP), which is an evolutionary algorithm that evolves models as syntax trees. While some abstract high-level genetic algorithm packages, such as GeneticAlgorithms.jl, already exist for Julia, this package is not optimized for genetic programming, and I provide a relatively fast implementation here by utilizing the low-level Expr Julia type. The resulting GP implementation has a simple programmatic interface that provides ample access to the parameters controlling the evolution. Finally, I provide the option for the GP to run in parallel using the highly scalable ”island model” for genetic algorithms, which has been shown to improve search results in a variety of genetic algorithms by maintaining solution diversity and explorative dynamics across the global population of solutions.