Implementing Parallel Genetic Algorithm Using Concurrent-functional Languages

Abstract

The spread of multiprocessor and multi-core architectures have a pervasive effect on the way software is developed. In order to take full advantage of them, a parallel implementation of every single program would be needed, but also a radical reformulation of the algorithms that are more appropriate to that kind of implementation. In this work we design and implement an evolutionary computation model using programming languages with built-in concurrent concepts. This article shows the advantages of these paradigms in order to implement a parallel genetic algorithm (pGA) with an island pools based topology in the concurrent-functional oriented programming languages: Erlang, Scala, and Clojure. Some implementation decisions are analyzed and the results of the solution of a study case are shown.