Publication detail

Computational and Exploratory Landscape Analysis of the GKLS Generator

KŮDELA, J. JUŘÍČEK, M.

Original Title

Computational and Exploratory Landscape Analysis of the GKLS Generator

Type

conference paper

Language

English

Original Abstract

The GKLS generator is one of the most used testbeds for benchmarking global optimization algorithms. In this paper, we conduct both a computational analysis and the Exploratory Landscape Analysis (ELA) of the GKLS generator. We utilize both canonically used and newly generated classes of GKLS-generated problems and show their use in benchmarking three state-of-the-art methods (from evolutionary and deterministic communities) in dimensions 5 and 10. We show that the GKLS generator produces "needle in a haystack" type problems that become extremely difficult to optimize in higher dimensions. We also conduct the ELA on the GKLS generator and then compare it to the ELA of two other widely used benchmark sets (BBOB and CEC 2014), and discuss the results.

Keywords

Benchmarking; Exploratory Landscape Analysis; GKLS; Global optimization; Black-box optimization

Authors

KŮDELA, J.; JUŘÍČEK, M.

Released

24. 7. 2023

Publisher

Association for Computing Machinery

Location

New York, NY, United States

ISBN

979-8-4007-0120-7

Book

GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation

Pages from

443

Pages to

446

Pages count

4

URL

https://dl.acm.org/doi/10.1145/3583133.3590653

BibTex

@inproceedings{BUT187607,
  author="Jakub {Kůdela} and Martin {Juříček}",
  title="Computational and Exploratory Landscape Analysis of the GKLS Generator",
  booktitle="GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation",
  year="2023",
  pages="443--446",
  publisher="Association for Computing Machinery",
  address="New York, NY, United States",
  doi="10.1145/3583133.3590653",
  isbn="979-8-4007-0120-7",
  url="https://dl.acm.org/doi/10.1145/3583133.3590653"
}