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Evolutionary Search for Stochastic Optimization with Binary Choice Relations Under Fuzzy Modeling | Journal of Computational and Cognitive Engineering
<!DOCTYPE html> <html lang="en" xml:lang="en"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title> Evolutionary Search for Stochastic Optimization with Binary Choice Relations Under Fuzzy Modeling | Journal of Computational and Cognitive Engineering </title> <link rel="icon" href="https://ojs.bonviewpress.com/public/journals/4/favicon_en_US.png"> <meta name="generator" content="Open Journal Systems 3.4.0.7"> <meta name="gs_meta_revision" content="1.1"/> <meta name="citation_journal_title" content="Journal of Computational and Cognitive Engineering"/> <meta name="citation_journal_abbrev" content="JCCE"/> <meta name="citation_issn" content="2810-9503"/> <meta name="citation_author" content="Vyacheslav Irodov"/> <meta name="citation_author_institution" content="Department of Information Technology, Dnipro Technological University, Ukraine"/> <meta name="citation_author" content="Serhii Dubrovskyi"/> <meta name="citation_author_institution" content="Department of Information Technology, Dnipro Technological University, Ukraine"/> <meta name="citation_author" content="Kostiantin Dudkin"/> <meta name="citation_author_institution" content="Department of Information Technology, Dnipro Technological University, Ukraine"/> <meta name="citation_author" content="Dmytro Chirin"/> <meta name="citation_author_institution" content="Department of Information Technology, Dnipro Technological University, Ukraine"/> <meta name="citation_author" content="Yuliya Aldrich"/> <meta name="citation_author_institution" content="Department of Information Technology, Dnipro Technological University, Ukraine"/> <meta name="citation_title" content="Evolutionary Search for Stochastic Optimization with Binary Choice Relations Under Fuzzy Modeling"/> <meta name="citation_language" content="en"/> <meta name="citation_date" content="2024/11/22"/> <meta name="citation_volume" content="3"/> <meta name="citation_issue" content="4"/> <meta name="citation_firstpage" content="412"/> <meta name="citation_lastpage" content="420"/> <meta name="citation_doi" content="10.47852/bonviewJCCE42022658"/> <meta name="citation_abstract_html_url" content="https://ojs.bonviewpress.com/index.php/JCCE/article/view/2658"/> <meta name="citation_abstract" xml:lang="en" content="The article is devoted to presenting an approach to decision-making in fuzzy modeling of systems based on a limited number of experiments characterizing the system's behavior. An iterative algorithm is proposed for use, in which the functions of generation and selection of solutions with several branches of evolutionary search are successively implemented. The generation function is built, for the most part, regardless of the content of the task. The selection function is built using a selection procedure that is completely dependent on the problem to be solved. The resulting information is used to guide the search process, making it understandable for guided machine learning. The convergence of algorithms for finding optimal solutions in the presence of constraints in the form of inequalities and additional constraints in the form of binary relations is analyzed. The results of solving test problems of stochastic optimization are given. The described approach solves the problem of fuzzy modeling for decision-making based on a limited set of experimental data, which makes it possible to identify regularities and generalize them to evaluate the performance and accuracy of machine learning algorithms. Received: 21 February 2024 | Revised: 1 April 2024 | Accepted: 29 April 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Vyacheslav Irodov: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review &amp; editing. Serhii Dubrovskyi: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review &amp; editing. Kostiantin Dudkin: Validation, Investigation, Resources. Dmytro Chirin: Validation, Resources. Yuliya Aldrich: Validation, Formal analysis. "/> <meta name="citation_keywords" xml:lang="en" content="evolutionary search"/> <meta name="citation_keywords" xml:lang="en" content="stochastic optimization"/> <meta name="citation_keywords" xml:lang="en" content="binary choice ratios"/> <meta name="citation_keywords" xml:lang="en" content="engineering"/> <meta name="citation_keywords" xml:lang="en" content="machine learning"/> <meta name="citation_pdf_url" content="https://ojs.bonviewpress.com/index.php/JCCE/article/download/2658/966"/> <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/" /> <meta name="DC.Creator.PersonalName" content="Vyacheslav Irodov"/> <meta name="DC.Creator.PersonalName" content="Serhii Dubrovskyi"/> <meta name="DC.Creator.PersonalName" content="Kostiantin Dudkin"/> <meta name="DC.Creator.PersonalName" content="Dmytro Chirin"/> <meta name="DC.Creator.PersonalName" content="Yuliya Aldrich"/> <meta name="DC.Date.created" scheme="ISO8601" content="2024-11-22"/> <meta name="DC.Date.dateSubmitted" scheme="ISO8601" content="2024-02-21"/> <meta name="DC.Date.issued" scheme="ISO8601" content="2024-11-22"/> <meta name="DC.Date.modified" scheme="ISO8601" content="2024-11-22"/> <meta name="DC.Description" xml:lang="en" content="The article is devoted to presenting an approach to decision-making in fuzzy modeling of systems based on a limited number of experiments characterizing the system's behavior. An iterative algorithm is proposed for use, in which the functions of generation and selection of solutions with several branches of evolutionary search are successively implemented. The generation function is built, for the most part, regardless of the content of the task. The selection function is built using a selection procedure that is completely dependent on the problem to be solved. The resulting information is used to guide the search process, making it understandable for guided machine learning. The convergence of algorithms for finding optimal solutions in the presence of constraints in the form of inequalities and additional constraints in the form of binary relations is analyzed. The results of solving test problems of stochastic optimization are given. The described approach solves the problem of fuzzy modeling for decision-making based on a limited set of experimental data, which makes it possible to identify regularities and generalize them to evaluate the performance and accuracy of machine learning algorithms. Received: 21 February 2024 | Revised: 1 April 2024 | Accepted: 29 April 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Vyacheslav Irodov: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review &amp; editing. Serhii Dubrovskyi: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review &amp; editing. Kostiantin Dudkin: Validation, Investigation, Resources. Dmytro Chirin: Validation, Resources. Yuliya Aldrich: Validation, Formal analysis. "/> <meta name="DC.Format" scheme="IMT" content="application/pdf"/> <meta name="DC.Identifier" content="2658"/> <meta name="DC.Identifier.pageNumber" content="412-420"/> <meta name="DC.Identifier.DOI" content="10.47852/bonviewJCCE42022658"/> <meta name="DC.Identifier.URI" content="https://ojs.bonviewpress.com/index.php/JCCE/article/view/2658"/> <meta name="DC.Language" scheme="ISO639-1" content="en"/> <meta name="DC.Rights" content="Copyright (c) 2024 Authors"/> <meta name="DC.Rights" content="https://creativecommons.org/licenses/by/4.0/"/> <meta name="DC.Source" content="Journal of Computational and Cognitive Engineering"/> <meta name="DC.Source.ISSN" content="2810-9503"/> <meta name="DC.Source.Issue" content="4"/> <meta name="DC.Source.Volume" content="3"/> <meta name="DC.Source.URI" content="https://ojs.bonviewpress.com/index.php/JCCE"/> <meta name="DC.Subject" xml:lang="en" content="evolutionary search"/> <meta name="DC.Subject" xml:lang="en" content="stochastic optimization"/> 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id="pkp_content_main"></a> <div class="page page_article"> <nav class="cmp_breadcrumbs" role="navigation" aria-label="You are here:"> <ol> <li> <a href="https://ojs.bonviewpress.com/index.php/JCCE/index"> Home </a> <span class="separator">/</span> </li> <li> <a href="https://ojs.bonviewpress.com/index.php/JCCE/issue/archive"> Archives </a> <span class="separator">/</span> </li> <li> <a href="https://ojs.bonviewpress.com/index.php/JCCE/issue/view/101"> Vol. 3 No. 4 (2024) </a> <span class="separator">/</span> </li> <li class="current" aria-current="page"> <span aria-current="page"> Research Articles </span> </li> </ol> </nav> <article class="obj_article_details"> <h1 class="page_title"> Evolutionary Search for Stochastic Optimization with Binary Choice Relations Under Fuzzy Modeling </h1> <div class="row"> <div class="main_entry"> <section class="item authors"> <h2 class="pkp_screen_reader">Authors</h2> <ul class="authors"> <li> <span class="name"> Vyacheslav Irodov </span> <span class="affiliation"> Department of Information Technology, Dnipro Technological University, Ukraine </span> <span class="orcid"> <svg class="orcid_icon" viewBox="0 0 256 256" aria-hidden="true"> <style type="text/css"> .st0{fill:#A6CE39;} .st1{fill:#FFFFFF;} </style> <path class="st0" d="M256,128c0,70.7-57.3,128-128,128C57.3,256,0,198.7,0,128C0,57.3,57.3,0,128,0C198.7,0,256,57.3,256,128z"/> <g> <path class="st1" d="M86.3,186.2H70.9V79.1h15.4v48.4V186.2z"/> <path class="st1" d="M108.9,79.1h41.6c39.6,0,57,28.3,57,53.6c0,27.5-21.5,53.6-56.8,53.6h-41.8V79.1z M124.3,172.4h24.5 c34.9,0,42.9-26.5,42.9-39.7c0-21.5-13.7-39.7-43.7-39.7h-23.7V172.4z"/> <path class="st1" d="M88.7,56.8c0,5.5-4.5,10.1-10.1,10.1c-5.6,0-10.1-4.6-10.1-10.1c0-5.6,4.5-10.1,10.1-10.1 C84.2,46.7,88.7,51.3,88.7,56.8z"/> </g> </svg> <a href="https://orcid.org/0000-0001-8772-9862" target="_blank"> https://orcid.org/0000-0001-8772-9862 </a> </span> </li> <li> <span class="name"> Serhii Dubrovskyi </span> <span class="affiliation"> Department of Information Technology, Dnipro Technological University, Ukraine </span> <span class="orcid"> <svg class="orcid_icon" viewBox="0 0 256 256" aria-hidden="true"> <style type="text/css"> .st0{fill:#A6CE39;} .st1{fill:#FFFFFF;} </style> <path class="st0" d="M256,128c0,70.7-57.3,128-128,128C57.3,256,0,198.7,0,128C0,57.3,57.3,0,128,0C198.7,0,256,57.3,256,128z"/> <g> <path class="st1" d="M86.3,186.2H70.9V79.1h15.4v48.4V186.2z"/> <path class="st1" d="M108.9,79.1h41.6c39.6,0,57,28.3,57,53.6c0,27.5-21.5,53.6-56.8,53.6h-41.8V79.1z M124.3,172.4h24.5 c34.9,0,42.9-26.5,42.9-39.7c0-21.5-13.7-39.7-43.7-39.7h-23.7V172.4z"/> <path class="st1" d="M88.7,56.8c0,5.5-4.5,10.1-10.1,10.1c-5.6,0-10.1-4.6-10.1-10.1c0-5.6,4.5-10.1,10.1-10.1 C84.2,46.7,88.7,51.3,88.7,56.8z"/> </g> </svg> <a href="https://orcid.org/0000-0001-6957-6620" target="_blank"> https://orcid.org/0000-0001-6957-6620 </a> </span> </li> <li> <span class="name"> Kostiantin Dudkin </span> <span class="affiliation"> Department of Information Technology, Dnipro Technological University, Ukraine </span> </li> <li> <span class="name"> Dmytro Chirin </span> <span class="affiliation"> Department of Information Technology, Dnipro Technological University, Ukraine </span> </li> <li> <span class="name"> Yuliya Aldrich </span> <span class="affiliation"> Department of Information Technology, Dnipro Technological University, Ukraine </span> </li> </ul> </section> <section class="item doi"> <h2 class="label"> DOI: </h2> <span class="value"> <a href="https://doi.org/10.47852/bonviewJCCE42022658"> https://doi.org/10.47852/bonviewJCCE42022658 </a> </span> </section> <section class="item keywords"> <h2 class="label"> Keywords: </h2> <span class="value"> evolutionary search, stochastic optimization, binary choice ratios, engineering, machine learning </span> </section> <section class="item abstract"> <h2 class="label">Abstract</h2> <p>The article is devoted to presenting an approach to decision-making in fuzzy modeling of systems based on a limited number of experiments characterizing the system's behavior. An iterative algorithm is proposed for use, in which the functions of generation and selection of solutions with several branches of evolutionary search are successively implemented. The generation function is built, for the most part, regardless of the content of the task. The selection function is built using a selection procedure that is completely dependent on the problem to be solved. The resulting information is used to guide the search process, making it understandable for guided machine learning. The convergence of algorithms for finding optimal solutions in the presence of constraints in the form of inequalities and additional constraints in the form of binary relations is analyzed. The results of solving test problems of stochastic optimization are given. The described approach solves the problem of fuzzy modeling for decision-making based on a limited set of experimental data, which makes it possible to identify regularities and generalize them to evaluate the performance and accuracy of machine learning algorithms.</p> <p> </p> <p><strong>Received</strong>: 21 February 2024 | <strong>Revised</strong>: 1 April 2024 | <strong>Accepted</strong>: 29 April 2024</p> <p> </p> <p><strong>Conflicts of Interest</strong></p> <p>The authors declare that they have no conflicts of interest to this work.</p> <p> </p> <p><strong>Data Availability Statement</strong></p> <p>Data sharing is not applicable to this article as no new data were created or analyzed in this study.</p> <p> </p> <p><strong>Author Contribution Statement</strong></p> <p><strong>Vyacheslav Irodov:</strong> Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. <strong>Serhii Dubrovskyi:</strong> Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing. <strong>Kostiantin Dudkin:</strong> Validation, Investigation, Resources. <strong>Dmytro Chirin:</strong> Validation, Resources. <strong>Yuliya Aldrich:</strong> Validation, Formal analysis.</p> <p> </p> <p> </p> <p> </p> </section> <br /><div class="separator"></div><div class="item abstract" id="trendmd-suggestions"></div><script defer src='//js.trendmd.com/trendmd.min.js' data-trendmdconfig='{"website_id":"89267", "element":"#trendmd-suggestions"}'></script><div class="item downloads_chart"> <h3 class="label"> Metrics </h3> <div id="paperbuzz"><div id="loading">Metrics Loading ...</div></div> <script type="text/javascript"> window.onload = function () { var options = { paperbuzzStatsJson: JSON.parse('{\"altmetrics_sources\":[],\"crossref_event_data_url\":\"https:\\/\\/api.eventdata.crossref.org\\/v1\\/events?rows=1000&filter=from-collected-date:1990-01-01,until-collected-date:2099-01-01,obj-id:10.47852\\/bonviewjcce42022658\",\"doi\":\"10.47852\\/bonviewjcce42022658\",\"metadata\":{\"DOI\":\"10.47852\\/bonviewjcce42022658\",\"ISSN\":[\"2810-9503\"],\"URL\":\"http:\\/\\/dx.doi.org\\/10.47852\\/bonviewjcce42022658\",\"abstract\":\"<jats:p>The article is devoted to presenting an approach to decision-making in fuzzy modeling of systems based on a limited number of experiments characterizing the system\\u2019s behavior. 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