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jMetal is a Java-based framework for multi-objective optimization
with metaheuristics providing, among other features, a wide set of
algorithms that are representative of the state-of-the-art. Although
it has become a widely used tool in the area, it lacks support for
automatic tuning of algorithm parameter settings, which can prevent
obtaining accurate Pareto front approximations, especially
for inexperienced users. In this paper, we present a first approach
to combine jMetal and irace, a package for automatic algorithm
configuration; the NSGA-II is chosen as the target algorithm to
be tuned. The goal is to facilitate the combined use of both tools
to jMetal users to avoid wasting time in adjusting manually the
parameters of the algorithms. Our proposal involves the definition
of a new algorithm template for evolutionary algorithms, which
allows the flexible composition of multi-objective evolutionary algorithms
from a set of configurable components, as well as the
generation of configuration files for adjusting the algorithm parameters
with irace. To validate our approach, NSGA-II is tuned
with a benchmark problems and compared with the same algorithm
using standard settings, resulting in a new variant that shows a
competitive behavior.Ministerio de Educación y Ciencia TIN2017-86049-RJunta de Andalucía P12-TIC-151
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