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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

8262-8278

Kód UT WoS článku

000807214200001

EID výsledku v databázi Scopus

2-s2.0-85123368430