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
Full text in the Digital Library
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"
}