Language Education Optimization: A New Human-Based 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%3A50019786" target="_blank" >RIV/62690094:18470/23:50019786 - isvavai.cz</a>
Result on the web
<a href="https://www.techscience.com/CMES/online/detail/18963" target="_blank" >https://www.techscience.com/CMES/online/detail/18963</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.32604/cmes.2023.025908" target="_blank" >10.32604/cmes.2023.025908</a>
Alternative languages
Result language
angličtina
Original language name
Language Education Optimization: A New Human-Based Metaheuristic Algorithm for Solving Optimization Problems
Original language description
In this paper, based on the concept of the NFL theorem, that there is no unique algorithm that has the best performance for all optimization problems, a new human-based metaheuristic algorithm called Language Education Optimization (LEO) is introduced, which is used to solve optimization problems. LEO is inspired by the foreign language education process in which a language teacher trains the students of language schools in the desired language skills and rules. LEO is mathematically modeled in three phases: (i) students selecting their teacher, (ii) students learning from each other, and (iii) individual practice, considering exploration in local search and exploitation in local search. The performance of LEO in optimization tasks has been challenged against fifty-two benchmark functions of a variety of unimodal, multimodal types and the CEC 2017 test suite. The optimization results show that LEO, with its acceptable ability in exploration, exploitation, and maintaining a balance between them, has efficient performance in optimization applications and solution presentation. LEO efficiency in optimization tasks is compared with ten well-known metaheuristic algorithms. Analyses of the simulation results show that LEO has effective performance in dealing with optimization tasks and is significantly superior and more competitive in combating the compared algorithms. The implementation results of the proposed approach to four engineering design problems show the effectiveness of LEO 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
S - Specificky vyzkum na vysokych skolach
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
Computer Modeling in Engineering & Sciences
ISSN
1526-1492
e-ISSN
1526-1506
Volume of the periodical
136
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
47
Pages from-to
1527-1573
UT code for WoS article
000892329200001
EID of the result in the Scopus database
2-s2.0-85148240247