Evaluation of Marine predator algorithm by using engineering optimisation problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F23%3AA2402M75" target="_blank" >RIV/61988987:17310/23:A2402M75 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2227-7390/11/23/4716" target="_blank" >https://www.mdpi.com/2227-7390/11/23/4716</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/math11234716" target="_blank" >10.3390/math11234716</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Evaluation of Marine predator algorithm by using engineering optimisation problems

Popis výsledku v původním jazyce

Real application of popular swarm-intelligence optimisation method is proposed. Four crucial numerical parameters of the Marine predators algorithm (MPA) are analysed to propose a proper setting to solve engineering problems. Besides population size, particle velocity parameter P, Lévy flight parameter β, and Fish aggregating devices (FADs) probability are studied. Finally, 193 various combinations of fixed and dynamic settings of the MPA parameters are experimentally compared when solving 13 engineering problems. The results are statistically analysed to highlight significant differences. Two out of four studied parameters significantly influence MPA performance. Three newly proposed MPA settings outperform the original variant significantly. Several recommendations for MPA setting on real applications were made. The original algorithms and their enhanced variants are compared on several examples of piecewise linearization problems. The results show that the enhanced approach performs sufficiently better when it creates a very promising approximation of functions. On the second thought, the degree of precision is slightly decreased by the focus on the speed of the optimization process.

Název v anglickém jazyce

Evaluation of Marine predator algorithm by using engineering optimisation problems

Popis výsledku anglicky

Real application of popular swarm-intelligence optimisation method is proposed. Four crucial numerical parameters of the Marine predators algorithm (MPA) are analysed to propose a proper setting to solve engineering problems. Besides population size, particle velocity parameter P, Lévy flight parameter β, and Fish aggregating devices (FADs) probability are studied. Finally, 193 various combinations of fixed and dynamic settings of the MPA parameters are experimentally compared when solving 13 engineering problems. The results are statistically analysed to highlight significant differences. Two out of four studied parameters significantly influence MPA performance. Three newly proposed MPA settings outperform the original variant significantly. Several recommendations for MPA setting on real applications were made. The original algorithms and their enhanced variants are compared on several examples of piecewise linearization problems. The results show that the enhanced approach performs sufficiently better when it creates a very promising approximation of functions. On the second thought, the degree of precision is slightly decreased by the focus on the speed of the optimization process.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Mathematics

ISSN

2227-7390

e-ISSN

—

Svazek periodika

—

Číslo periodika v rámci svazku

23

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

19

Strana od-do

—

Kód UT WoS článku

001116971600001

EID výsledku v databázi Scopus

2-s2.0-85179300432