Evolutionary Computation with Islands: Extending EvoLP.jl for Parallel Computing

Paper at the 35th Norwegian ICT Conference for Research and Education


The use of evolutionary computation for optimisation is a relevant area of research in many fields of science and the industry, where complex problems are frequently encountered. As an effort to support the research in this niche, we present an extension for EvoLP.jl: the evolutionary computation playground in Julia, that includes three new operators for implementing island models for genetic algorithms. The extension enables the framework to run using the Message Passing Interface protocol, an international standard for communication in parallel architectures that is available in most high performance computing clusters today. We study the advantages of the implementation by performing a series of tests on well-known numerical optimisation benchmarks of various difficulties and on several dimensions. Both the code and the data are available in a GitHub repository. This work enables researchers to implement powerful parallel evolutionary algorithms without moving away from the high level of abstraction that the framework provides.

NIKT: Norsk IKT-konferanse for forskning og utdanning
Xavier F. C. Sánchez Díaz
Xavier F. C. Sánchez Díaz
PhD candidate in Artificial Intelligence

PhD candidate in Artificial Intelligence at the Department of Computer Science (IDI) of the Norwegian University of Science and Technology