Multijob
Robin Mueller-Bady, Martin Kappes, Lukas Atkinson, Inmaculada Medina‐Bulo · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2017
An important challenge in designing evolutionary search heuristics is the statistically significant evaluation of different configurations. The goal is to find an optimal algorithm design with respect to its parameters, i.e., parameter tuning. In this paper, we propose an open source software framework, called Multijob, allowing to simplify and automate EA configuration and parameter tuning. Additionally, the framework offers a workflow for distributed execution of the preconfigured algorithms in heterogeneous computing clusters or grids.