Publication detail

New Benchmark Functions for Single-Objective Optimization Based on a Zigzag Pattern

KŮDELA, J. MATOUŠEK, R.

Original Title

New Benchmark Functions for Single-Objective Optimization Based on a Zigzag Pattern

Type

journal article in Web of Science

Language

English

Original Abstract

Benchmarking plays a crucial role in both development of new optimization methods, and in conducting proper comparisons between already existing methods, particularly in the field of evolutionary computation. In this paper, we develop new benchmark functions for bound-constrained single-objective optimization that are based on a zigzag function. The proposed zigzag function has three parameters that control its behaviour and difficulty of the resulting problems. Utilizing the zigzag function, we introduce four new functions and conduct extensive computational experiments to evaluate their performance as benchmarks. The experiments comprise of using the newly proposed functions in 100 different parameter settings for the comparison of eight different optimization algorithms, which are a mix of canonical methods and best performing methods from the Congress on Evolutionary Computation competitions. Using the results from the computational comparison, we choose some of the parametrization of the newly proposed functions to devise an ambiguous benchmark set in which each of the problems introduces a statistically significant ranking among the algorithms, but the ranking for the entire set is ambiguous with no clear dominating relationship between the algorithms. We also conduct an exploratory landscape analysis of the newly proposed benchmark functions and compare the results with the benchmark functions used in the Black-Box-Optimization-Benchmarking suite. The results suggest that the new benchmark functions are well suited for algorithmic comparisons.

Keywords

numerical optimization; benchmarking; single objective problems; exploratory landscape analysis

Authors

KŮDELA, J.; MATOUŠEK, R.

Released

20. 1. 2022

Publisher

IEEE

ISBN

2169-3536

Periodical

IEEE Access

Year of study

10

Number

1

State

United States of America

Pages from

8262

Pages to

8278

Pages count

17

URL

https://ieeexplore.ieee.org/document/9684455

Full text in the Digital Library

http://hdl.handle.net/11012/203516

BibTex

@article{BUT176022,
  author="Jakub {Kůdela} and Radomil {Matoušek}",
  title="New Benchmark Functions for Single-Objective Optimization Based on a Zigzag Pattern",
  journal="IEEE Access",
  year="2022",
  volume="10",
  number="1",
  pages="8262--8278",
  doi="10.1109/ACCESS.2022.3144067",
  issn="2169-3536",
  url="https://ieeexplore.ieee.org/document/9684455"
}