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KŮDELA, J. JUŘÍČEK, M. PARÁK, R.
Original Title
A collection of robotics problems for benchmarking evolutionary computation methods
Type
conference paper
Language
English
Original Abstract
The utilization of benchmarking techniques has a crucial role in the development of novel optimization algorithms, and also in performing comparisons between already existing methods. This is especially true in the field of evolutionary computation, where the theoretical performance of the method is difficult to analyze. For these benchmarking purposes, artificial (or synthetic) functions are currently the most widely used ones. In this paper, we present a collection of real-world robotics problems that can be used for benchmarking evolutionary computation methods. The proposed benchmark problems are a combination of inverse kinematics and path planning in robotics that can be parameterized. We conducted an extensive numerical investigation that encompassed solving 200 benchmark problems by seven selected metaheuristic algorithms. The results of this investigation showed that the proposed benchmark problems are quite difficult (multimodal and non-separable) and that they can be successfully used for differentiating and ranking various metaheuristics.
Keywords
Evolutionary computation; Metaheuristics; Benchmarking; Robotics
Authors
KŮDELA, J.; JUŘÍČEK, M.; PARÁK, R.
Released
9. 4. 2023
Publisher
Springer
Location
Cham
ISBN
978-3-031-30229-9
Book
26th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of EvoStar 2023
0302-9743
Periodical
Lecture Notes in Computer Science
Year of study
13989
State
Federal Republic of Germany
Pages from
364
Pages to
379
Pages count
16
BibTex
@inproceedings{BUT183645, author="Jakub {Kůdela} and Martin {Juříček} and Roman {Parák}", title="A collection of robotics problems for benchmarking evolutionary computation methods", booktitle="26th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of EvoStar 2023", year="2023", journal="Lecture Notes in Computer Science", volume="13989", pages="364 --379", publisher="Springer", address="Cham", doi="10.1007/978-3-031-30229-9\{_}24", isbn="978-3-031-30229-9", issn="0302-9743" }