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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APU143121" target="_blank" >RIV/00216305:26210/22:PU143121 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/9684455" target="_blank" >https://ieeexplore.ieee.org/document/9684455</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2022.3144067" target="_blank" >10.1109/ACCESS.2022.3144067</a>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

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

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

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

Name of the periodical

IEEE Access

ISSN

2169-3536

e-ISSN

—

Volume of the periodical

10

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

17

Pages from-to

8262-8278

UT code for WoS article

000807214200001

EID of the result in the Scopus database

2-s2.0-85123368430