Detail publikace

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

KŮDELA, J.

Originální název

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

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Benchmarking; Black-box optimization; DIRECT-type methods

Autoři

KŮDELA, J.

Vydáno

24. 7. 2023

Nakladatel

Association for Computing Machinery

Místo

New York, NY, United States

ISBN

979-8-4007-0120-7

Kniha

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

Strany od

1620

Strany do

1627

Strany počet

8

URL

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

Plný text v Digitální knihovně

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"
}