Publication detail
Novel Zigzag-based Benchmark Functions for Bound Constrained Single Objective Optimization
KŮDELA, J.
English title
Novel Zigzag-based Benchmark Functions for Bound Constrained Single Objective Optimization
Type
conference paper
Language
en
Original abstract
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.
English abstract
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.
Keywords in English
benchmark functions; single objective optimization; zigzag function
Released
01.07.2021
Publisher
IEEE
ISBN
978-1-7281-8393-0
Book
2021 IEEE Congress on Evolutionary Computation (CEC)
Pages from–to
857–862
Pages count
6
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",
month="July",
pages="857--862",
publisher="IEEE",
isbn="978-1-7281-8393-0"
}