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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F21%3APU142804" target="_blank" >RIV/00216305:26210/21:PU142804 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/9504720" target="_blank" >https://ieeexplore.ieee.org/document/9504720</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CEC45853.2021.9504720" target="_blank" >10.1109/CEC45853.2021.9504720</a>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EF16_026%2F0008392" target="_blank" >EF16_026/0008392: Computer Simulations for Effective Low-Emission Energy Engineering</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2021 IEEE Congress on Evolutionary Computation (CEC)

ISBN

978-1-7281-8393-0

ISSN

—

e-ISSN

—

Number of pages

6

Pages from-to

857-862

Publisher name

IEEE

Place of publication

neuveden

Event location

Krakow

Event date

Jun 28, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000703866100108