Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F23%3A50020255" target="_blank" >RIV/62690094:18470/23:50020255 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0950705122011042" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0950705122011042</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.knosys.2022.110011" target="_blank" >10.1016/j.knosys.2022.110011</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems

Popis výsledku v původním jazyce

In this paper, a new metaheuristic algorithm called the Coati Optimization Algorithm (COA) is introduced, which mimics coati behavior in nature. The fundamental idea of COA is the simulation of the two natural behaviors of coatis: (i) their behavior when attacking and hunting iguanas and (ii) their escape from predators. The implementation steps of COA are described and mathematically modeled in two phases of exploration and exploitation. COA performance is evaluated on fifty-one objective functions, including twenty-nine functions from the IEEE CEC-2017 test suite and twenty-two real-world applications from the IEEE CEC-2011 test suite. COA&apos;s results are compared to those of eleven well-known metaheuristic algorithms. The simulation results indicate that COA has an evident superiority over the compared algorithms by balancing exploration in global search and exploitation in local search, and is far more competitive. To assess the COA&apos;s effectiveness in real-world applications, the proposed approach is implemented on the IEEE CEC-2011 test functions and four practical optimization problems, which the simulation results indicate the high capability of COA in dealing with these types of optimization problems.

Název v anglickém jazyce

Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems

Popis výsledku anglicky

In this paper, a new metaheuristic algorithm called the Coati Optimization Algorithm (COA) is introduced, which mimics coati behavior in nature. The fundamental idea of COA is the simulation of the two natural behaviors of coatis: (i) their behavior when attacking and hunting iguanas and (ii) their escape from predators. The implementation steps of COA are described and mathematically modeled in two phases of exploration and exploitation. COA performance is evaluated on fifty-one objective functions, including twenty-nine functions from the IEEE CEC-2017 test suite and twenty-two real-world applications from the IEEE CEC-2011 test suite. COA&apos;s results are compared to those of eleven well-known metaheuristic algorithms. The simulation results indicate that COA has an evident superiority over the compared algorithms by balancing exploration in global search and exploitation in local search, and is far more competitive. To assess the COA&apos;s effectiveness in real-world applications, the proposed approach is implemented on the IEEE CEC-2011 test functions and four practical optimization problems, which the simulation results indicate the high capability of COA in dealing with these types of optimization problems.

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

Knowledge-based systems

ISSN

0950-7051

e-ISSN

1872-7409

Svazek periodika

259

Číslo periodika v rámci svazku

January

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

43

Strana od-do

"Article Number: 110011"

Kód UT WoS článku

000934113200001

EID výsledku v databázi Scopus

2-s2.0-85141454474