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A Conceptual Comparison of Six Nature-Inspired Metaheuristic Algorithms in Process Optimization

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F22%3A10249735" target="_blank" >RIV/61989100:27230/22:10249735 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.webofscience.com/wos/woscc/full-record/WOS:000778142900001" target="_blank" >https://www.webofscience.com/wos/woscc/full-record/WOS:000778142900001</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/pr10020197" target="_blank" >10.3390/pr10020197</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Conceptual Comparison of Six Nature-Inspired Metaheuristic Algorithms in Process Optimization

  • Original language description

    In recent years, several high-performance nature-inspired metaheuristic algorithms have been proposed. It is important to study and compare the convergence, computational burden and statistical significance of these metaheuristics to aid future developments. This study focuses on six recent metaheuristics, namely, ant lion optimization (ALO), arithmetic optimization algorithm (AOA), dragonfly algorithm (DA), grey wolf optimizer (GWO), salp swarm algorithm (SSA) and whale optimization algorithm (WOA). Optimization of an industrial machining application is tackled in this paper. The optimal machining parameters (peak current, duty factor, wire tension and water pressure) of WEDM are predicted using the six aforementioned metaheuristics. The objective functions of the optimization study are to maximize the material removal rate (MRR) and minimize the wear ratio (WR) and surface roughness (SR). All of the current algorithms have been seen to surpass existing results, thereby indicating their superiority over conventional optimization algorithms.

  • 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

    20300 - Mechanical engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

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

    Processes

  • ISSN

    2227-9717

  • e-ISSN

    2227-9717

  • Volume of the periodical

    10

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    20

  • Pages from-to

    nestrankovano

  • UT code for WoS article

    000778142900001

  • EID of the result in the Scopus database

    2-s2.0-85124291857