Clouded Leopard Optimization: A New Nature-Inspired Optimization Algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F22%3A50019499" target="_blank" >RIV/62690094:18470/22:50019499 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9899451" target="_blank" >https://ieeexplore.ieee.org/document/9899451</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2022.3208700" target="_blank" >10.1109/ACCESS.2022.3208700</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Clouded Leopard Optimization: A New Nature-Inspired Optimization Algorithm

Popis výsledku v původním jazyce

This paper proposes a new nature-inspired metaheuristic algorithm called Clouded Leopard Optimization (CLO), which mimics the natural behavior of clouded leopards in the wild. The fundamental inspiration of CLO is derived from two ways of natural behaviors of the clouded leopard, including hunting strategy and daily resting on trees. CLO is mathematically modeled in two phases of exploration and exploitation, based on the simulation of these two natural behaviors. CLO performance is evaluated in solving sixty-eight benchmark functions, including unimodal, multimodal, CEC 2015, and CEC 2017 types. The performance of CLO in solving optimization problems is compared with the performance of ten famous metaheuristic algorithms. The simulation results show that the proposed CLO approach with high ability in exploration, exploitation, and balancing between them has a high capability in optimization applications. Simulation results show that CLO performs better in most test functions than competitor algorithms. In addition, the implementation of CLO on four engineering design issues demonstrates the capability of the proposed approach in real-world applications.

Název v anglickém jazyce

Clouded Leopard Optimization: A New Nature-Inspired Optimization Algorithm

Popis výsledku anglicky

This paper proposes a new nature-inspired metaheuristic algorithm called Clouded Leopard Optimization (CLO), which mimics the natural behavior of clouded leopards in the wild. The fundamental inspiration of CLO is derived from two ways of natural behaviors of the clouded leopard, including hunting strategy and daily resting on trees. CLO is mathematically modeled in two phases of exploration and exploitation, based on the simulation of these two natural behaviors. CLO performance is evaluated in solving sixty-eight benchmark functions, including unimodal, multimodal, CEC 2015, and CEC 2017 types. The performance of CLO in solving optimization problems is compared with the performance of ten famous metaheuristic algorithms. The simulation results show that the proposed CLO approach with high ability in exploration, exploitation, and balancing between them has a high capability in optimization applications. Simulation results show that CLO performs better in most test functions than competitor algorithms. In addition, the implementation of CLO on four engineering design issues demonstrates the capability of the proposed approach in real-world applications.

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

2169-3536

Svazek periodika

10

Číslo periodika v rámci svazku

Říjen 2022

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

31

Strana od-do

102876-102906

Kód UT WoS článku

000864147700001

EID výsledku v databázi Scopus

2-s2.0-85139440234