A new human-based metaheuristic algorithm for solving optimization problems on the base of simulation of driving training process

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F22%3A50019460" target="_blank" >RIV/62690094:18470/22:50019460 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.nature.com/articles/s41598-022-14225-7" target="_blank" >https://www.nature.com/articles/s41598-022-14225-7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-022-14225-7" target="_blank" >10.1038/s41598-022-14225-7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A new human-based metaheuristic algorithm for solving optimization problems on the base of simulation of driving training process

Popis výsledku v původním jazyce

In this paper, a new stochastic optimization algorithm is introduced, called Driving Training-Based Optimization (DTBO), which mimics the human activity of driving training. The fundamental inspiration behind the DTBO design is the learning process to drive in the driving school and the training of the driving instructor. DTBO is mathematically modeled in three phases: (1) training by the driving instructor, (2) patterning of students from instructor skills, and (3) practice. The performance of DTBO in optimization is evaluated on a set of 53 standard objective functions of unimodal, high-dimensional multimodal, fixed-dimensional multimodal, and IEEE CEC2017 test functions types. The optimization results show that DTBO has been able to provide appropriate solutions to optimization problems by maintaining a proper balance between exploration and exploitation. The performance quality of DTBO is compared with the results of 11 well-known algorithms. The simulation results show that DTBO performs better compared to 11 competitor algorithms and is more efficient in optimization applications.

Název v anglickém jazyce

A new human-based metaheuristic algorithm for solving optimization problems on the base of simulation of driving training process

Popis výsledku anglicky

In this paper, a new stochastic optimization algorithm is introduced, called Driving Training-Based Optimization (DTBO), which mimics the human activity of driving training. The fundamental inspiration behind the DTBO design is the learning process to drive in the driving school and the training of the driving instructor. DTBO is mathematically modeled in three phases: (1) training by the driving instructor, (2) patterning of students from instructor skills, and (3) practice. The performance of DTBO in optimization is evaluated on a set of 53 standard objective functions of unimodal, high-dimensional multimodal, fixed-dimensional multimodal, and IEEE CEC2017 test functions types. The optimization results show that DTBO has been able to provide appropriate solutions to optimization problems by maintaining a proper balance between exploration and exploitation. The performance quality of DTBO is compared with the results of 11 well-known algorithms. The simulation results show that DTBO performs better compared to 11 competitor algorithms and is more efficient in optimization applications.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50301 - Education, general; including training, pedagogy, didactics [and education systems]

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

Scientific reports

ISSN

2045-2322

e-ISSN

2045-2322

Svazek periodika

12

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

21

Strana od-do

"Article number: 9924"

Kód UT WoS článku

000909508300001

EID výsledku v databázi Scopus

2-s2.0-85132291232