AMBO: All Members-Based Optimizer for Solving Optimization Problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F22%3A50018488" target="_blank" >RIV/62690094:18470/22:50018488 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.techscience.com/cmc/v70n2/44661" target="_blank" >https://www.techscience.com/cmc/v70n2/44661</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.32604/cmc.2022.019867" target="_blank" >10.32604/cmc.2022.019867</a>

Jazyk výsledku

angličtina

Název v původním jazyce

AMBO: All Members-Based Optimizer for Solving Optimization Problems

Popis výsledku v původním jazyce

There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population -based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various opti-mization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst mem-ber) to update the population matrix. Therefore, in AMBO, any member of the population can play a role in updating the population matrix. The theory of AMBO is described and then mathematically modeled for implementation on optimization problems. The performance of the proposed algorithm is evaluated on a set of twenty-three standard objective functions, which belong to three different categories: unimodal, high-dimensional multimodal, and fixed-dimensional multimodal functions. In order to analyze and compare the optimization results for the mentioned objective functions obtained by AMBO, eight other well-known algorithms have been also implemented. The optimization results demonstrate the ability of AMBO to solve various opti-mization problems. Also, comparison and analysis of the results show that AMBO is superior and more competitive than the other mentioned algorithms in providing suitable solution.

Název v anglickém jazyce

AMBO: All Members-Based Optimizer for Solving Optimization Problems

Popis výsledku anglicky

There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population -based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various opti-mization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst mem-ber) to update the population matrix. Therefore, in AMBO, any member of the population can play a role in updating the population matrix. The theory of AMBO is described and then mathematically modeled for implementation on optimization problems. The performance of the proposed algorithm is evaluated on a set of twenty-three standard objective functions, which belong to three different categories: unimodal, high-dimensional multimodal, and fixed-dimensional multimodal functions. In order to analyze and compare the optimization results for the mentioned objective functions obtained by AMBO, eight other well-known algorithms have been also implemented. The optimization results demonstrate the ability of AMBO to solve various opti-mization problems. Also, comparison and analysis of the results show that AMBO is superior and more competitive than the other mentioned algorithms in providing suitable solution.

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

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

CMC-Computers, Materials &amp; Continua

ISSN

1546-2218

e-ISSN

1546-2226

Svazek periodika

70

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

2905-2921

Kód UT WoS článku

000705964000012

EID výsledku v databázi Scopus

2-s2.0-85116003060