AMBO: All Members-Based Optimizer for Solving Optimization Problems
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
AMBO: All Members-Based Optimizer for Solving Optimization Problems
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
CMC-Computers, Materials & Continua
ISSN
1546-2218
e-ISSN
1546-2226
Volume of the periodical
70
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
2905-2921
UT code for WoS article
000705964000012
EID of the result in the Scopus database
2-s2.0-85116003060