Osprey optimization algorithm: A new bio-inspired metaheuristic algorithm for solving engineering optimization problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F23%3A50020225" target="_blank" >RIV/62690094:18470/23:50020225 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.frontiersin.org/articles/10.3389/fmech.2022.1126450/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fmech.2022.1126450/full</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/fmech.2022.1126450" target="_blank" >10.3389/fmech.2022.1126450</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Osprey optimization algorithm: A new bio-inspired metaheuristic algorithm for solving engineering optimization problems

Popis výsledku v původním jazyce

This paper introduces a new metaheuristic algorithm named the Osprey Optimization Algorithm (OOA), which imitates the behavior of osprey in nature. The fundamental inspiration of OOA is the strategy of ospreys when hunting fish from the seas. In this hunting strategy, the osprey hunts the prey after detecting its position, then carries it to a suitable position to eat it. The proposed approach of OOA in two phases of exploration and exploitation is mathematically modeled based on the simulation of the natural behavior of ospreys during the hunting process. The performance of OOA has been evaluated in the optimization of twenty-nine standard benchmark functions from the CEC 2017 test suite. Furthermore, the performance of OOA is compared with the performance of twelve well-known metaheuristic algorithms. The simulation results show that the proposed OOA has provided superior performance compared to competitor algorithms by maintaining the balance between exploration and exploitation. In addition, the implementation of OOA on twenty-two real-world constrained optimization problems from the CEC 2011 test suite shows the high capability of the proposed approach in optimizing real-world applications.

Název v anglickém jazyce

Osprey optimization algorithm: A new bio-inspired metaheuristic algorithm for solving engineering optimization problems

Popis výsledku anglicky

This paper introduces a new metaheuristic algorithm named the Osprey Optimization Algorithm (OOA), which imitates the behavior of osprey in nature. The fundamental inspiration of OOA is the strategy of ospreys when hunting fish from the seas. In this hunting strategy, the osprey hunts the prey after detecting its position, then carries it to a suitable position to eat it. The proposed approach of OOA in two phases of exploration and exploitation is mathematically modeled based on the simulation of the natural behavior of ospreys during the hunting process. The performance of OOA has been evaluated in the optimization of twenty-nine standard benchmark functions from the CEC 2017 test suite. Furthermore, the performance of OOA is compared with the performance of twelve well-known metaheuristic algorithms. The simulation results show that the proposed OOA has provided superior performance compared to competitor algorithms by maintaining the balance between exploration and exploitation. In addition, the implementation of OOA on twenty-two real-world constrained optimization problems from the CEC 2011 test suite shows the high capability of the proposed approach in optimizing real-world applications.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20301 - Mechanical engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Frontiers in Mechanical Engineering

ISSN

2297-3079

e-ISSN

2297-3079

Svazek periodika

8

Číslo periodika v rámci svazku

January

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

43

Strana od-do

"Article Number: 1126450"

Kód UT WoS článku

000925502800001

EID výsledku v databázi Scopus

2-s2.0-85147388943