Publication detail

Benchmarking State-of-the-art DIRECT-type Methods on the BBOB Noiseless Testbed

KŮDELA, J.

Original Title

Benchmarking State-of-the-art DIRECT-type Methods on the BBOB Noiseless Testbed

Type

conference paper

Language

English

Original Abstract

In recent years, there has been significant progress in the development of new DIRECT-type algorithms for black-box optimization problems. In this paper, we evaluate three well-performing DIRECT-type methods from a recent extensive numerical study on the BBOB noiseless testbed in dimensions 2, 3, 5, 10, and 20. We discuss the strengths and weaknesses of these algorithms on different classes of functions and provide a comparison with the original DIRECT method, as well as with three other well-established methods: RL-SHADE, L-BFGS-B, and SLSQP.

Keywords

Benchmarking; Black-box optimization; DIRECT-type methods

Authors

KŮDELA, J.

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

1620

Pages to

1627

Pages count

8

URL

https://dl.acm.org/doi/abs/10.1145/3583133.3596308

Full text in the Digital Library

http://hdl.handle.net/11012/245017

BibTex

@inproceedings{BUT187594,
  author="Jakub {Kůdela}",
  title="Benchmarking State-of-the-art DIRECT-type Methods on the BBOB Noiseless Testbed",
  booktitle="GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation",
  year="2023",
  pages="1620--1627",
  publisher="Association for Computing Machinery",
  address="New York, NY, United States",
  doi="10.1145/3583133.3596308",
  isbn="979-8-4007-0120-7",
  url="https://dl.acm.org/doi/abs/10.1145/3583133.3596308"
}