Detail publikace

Novel Zigzag-based Benchmark Functions for Bound Constrained Single Objective Optimization

KŮDELA, J.

Originální název

Novel Zigzag-based Benchmark Functions for Bound Constrained Single Objective Optimization

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The development and comparison of new optimization methods in general, and evolutionary algorithms in particular, rely heavily on benchmarking. In this paper, the construction of novel zigzag-based benchmark functions for bound constrained single objective optimization is presented. The new benchmark functions are non-differentiable, highly multimodal, and have a built-in parameter that controls the complexity of the function. To investigate the properties of the new benchmark functions two of the best algorithms from the CEC'20 Competition on Single Objective Bound Constrained Optimization, as well as one standard evolutionary algorithm, were utilized in a computational study. The results of the study suggest that the new benchmark functions are very well suited for algorithmic comparison.

Klíčová slova

benchmark functions; single objective optimization; zigzag function

Autoři

KŮDELA, J.

Vydáno

1. 7. 2021

Nakladatel

IEEE

ISBN

978-1-7281-8393-0

Kniha

2021 IEEE Congress on Evolutionary Computation (CEC)

Strany od

857

Strany do

862

Strany počet

6

URL

https://ieeexplore.ieee.org/document/9504720

BibTex

@inproceedings{BUT175647,
  author="Jakub {Kůdela}",
  title="Novel Zigzag-based Benchmark Functions for Bound Constrained Single Objective Optimization",
  booktitle="2021 IEEE Congress on Evolutionary Computation (CEC)",
  year="2021",
  pages="857--862",
  publisher="IEEE",
  doi="10.1109/CEC45853.2021.9504720",
  isbn="978-1-7281-8393-0",
  url="https://ieeexplore.ieee.org/document/9504720"
}