All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • 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 &amp; 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