Minimizing evolutionary algorithms energy consumption in the low-level language Zig Merelo Guervós, Juan Julián Green computing Metaheuristic Energy-aware computing Evolutionary algorithms Zig Managing energy resources in scientific computing implies awareness of a wide range of software engineering techniques that, when applied, can minimize the energy footprint of experiments. In the case of evolutionary computation, we are talking about a specific workload that includes the generation of chromosomes and operations that change parts of them or access and operate on them to obtain a fitness value. In a low-level language such as Zig, we will show how different choices will affect the energy consumption of an experiment. 2024-05-21T07:29:01Z 2024-05-21T07:29:01Z 2024-05-19 conference output https://hdl.handle.net/10481/91923 eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional