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Automatic configuration of NSGA-II with jMetal and irace

Published:13 July 2019Publication History

ABSTRACT

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.

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        cover image ACM Conferences
        GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
        July 2019
        2161 pages
        ISBN:9781450367486
        DOI:10.1145/3319619

        Copyright © 2019 ACM

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        Publication History

        • Published: 13 July 2019

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