OOBO: A New Metaheuristic Algorithm 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%2F23%3A50020829" target="_blank" >RIV/62690094:18470/23:50020829 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2313-7673/8/6/468" target="_blank" >https://www.mdpi.com/2313-7673/8/6/468</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/biomimetics8060468" target="_blank" >10.3390/biomimetics8060468</a>
Alternative languages
Result language
angličtina
Original language name
OOBO: A New Metaheuristic Algorithm for Solving Optimization Problems
Original language description
This study proposes the One-to-One-Based Optimizer (OOBO), a new optimization technique for solving optimization problems in various scientific areas. The key idea in designing the suggested OOBO is to effectively use the knowledge of all members in the process of updating the algorithm population while preventing the algorithm from relying on specific members of the population. We use a one-to-one correspondence between the two sets of population members and the members selected as guides to increase the involvement of all population members in the update process. Each population member is chosen just once as a guide and is only utilized to update another member of the population in this one-to-one interaction. The proposed OOBO's performance in optimization is evaluated with fifty-two objective functions, encompassing unimodal, high-dimensional multimodal, and fixed-dimensional multimodal types, and the CEC 2017 test suite. The optimization results highlight the remarkable capacity of OOBO to strike a balance between exploration and exploitation within the problem-solving space during the search process. The quality of the optimization results achieved using the proposed OOBO is evaluated by comparing them to eight well-known algorithms. The simulation findings show that OOBO outperforms the other algorithms in addressing optimization problems and can give more acceptable quasi-optimal solutions. Also, the implementation of OOBO in six engineering problems shows the effectiveness of the proposed approach in solving real-world optimization applications.
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
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Biomimetics
ISSN
2313-7673
e-ISSN
2313-7673
Volume of the periodical
8
Issue of the periodical within the volume
6
Country of publishing house
CH - SWITZERLAND
Number of pages
48
Pages from-to
"Article number: 468"
UT code for WoS article
001094203000001
EID of the result in the Scopus database
2-s2.0-85175049974