A New Approach to Solve Fuzzy Linear Fractional Programming Problems via Rank Function of Trapezoidal Fuzzy Numbers

A New Approach to Solve Fuzzy Linear Fractional Programming Problems via Rank Function of Trapezoidal Fuzzy Numbers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A New Approach to Solve Fuzzy Linear Fractional Programming Problems via Rank Function of Trapezoidal Fuzzy Numbers Maher A. Nawkhass, Nejmaddin A. Sulaiman This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3134389/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Ranking fuzzy numbers is essential to descriptive decision-making and several other fuzzy systems and applications. Numerous techniques have been put forth to rank fuzzy numbers. It has been demonstrated that each of these approaches occasionally yields findings that are counterintuitive. The aim of this studies can be factors such as: firstly, Willingness to improve manufacturing production. Secondly, to minimize production time (negated iteration). Finally, the aspiration to discover new linear fuzzy script The study of “Fuzzy Linear Fractional Programming” FLFP problems with “trapezoidal fuzzy numbers” has been addressed in this research, where the constraints are actual numbers and the objective functions are fuzzy numbers. Obtaining the fuzzy optimum solution with unconstrained variables and parameters has been made possible in this study by the introduction of a modern, effective strategy for the FLFP problems. The newly employed transformation methodology is similarly based on the suggested method of crisp linear fractional programming foundation. To get an ideal answer, a computational method has been provided. A real-world example has been given to show the effectiveness of our suggested methodology. Fuzzy Set Fuzzy Number Trapezoidal Fuzzy Number Ranking Function Fuzzy Linear Fractional Programming Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3134389","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":215189615,"identity":"7c68b344-6f0b-44cb-aa18-2cbc81f0944f","order_by":0,"name":"Maher A. 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