On the potential of automated algorithm configuration on multi-modal multi-objective optimization problems

Jeroen Rook, Heike Trautmann, Jakob Bossek, Christian Grimme

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

10 Downloads (Pure)

Abstract

Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e.g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.
Original languageEnglish
Title of host publicationGECCO '22
Subtitle of host publicationProceedings of the Genetic and Evolutionary Computation Conference Companion
Pages356-359
Number of pages4
ISBN (Electronic)978-1-4503-9268-6
DOIs
Publication statusPublished - 9 Jul 2022

Fingerprint

Dive into the research topics of 'On the potential of automated algorithm configuration on multi-modal multi-objective optimization problems'. Together they form a unique fingerprint.

Cite this