Distinctive representations of icosagonal fuzzy numbers along with novel defuzzification techniques for solving fuzzy assignment problems

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This study introduces novel representations and defuzzification techniques for icosagonal fuzzy numbers to solve fuzzy assignment problems, including a proposed ranking function.

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This paper develops multiple representations of icosagonal fuzzy numbers (symmetric/asymmetric, linear/non-linear, and both single-valued and interval-valued) and introduces defuzzification procedures using centroid-based, alpha-cut mean, and bounded area approaches. It also proposes a ranking function for comparing icosagonal fuzzy numbers and applies these methods to a numerical fuzzy assignment problem modeled on an interview board panel with twenty parameters, using linguistic terms to represent ambiguous information. The study is presented as a Research Square preprint and explicitly notes it has not been peer reviewed. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

In this paper, we represent icosagonal fuzzy numbers in a variety ofways, both symmetrically and asymmetrically, linearly and non-linearly as well as single valued and interval -valued. Along with this, we have alsodeveloped some defuzzification procedures with different approaches based on centroidmethod, the mean of alpha-cut method and bounded area method. In order todemonstrate the significance of these strategies, defuzzification approaches can be applied to many optimization problems in operational research. We have applied these strategies to solve the numerical example based on fuzzy assignment problem in the interview board panel with twenty parameters. This study deals with the situation where icosagonal fuzzynumbers are used to represent ambiguous information in the form of linguistic terms. The ranking function for icosagonal number is also proposed in this paper for the better comparison of two icosagonal fuzzy numbers and its primary goal is used in this research for the appropriate allocation to resolve the fuzzy assignment problem.
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Distinctive representations of icosagonal fuzzy numbers along with novel defuzzification techniques for solving fuzzy assignment problems | 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 Distinctive representations of icosagonal fuzzy numbers along with novel defuzzification techniques for solving fuzzy assignment problems Jaya Bhadauria, Suneel Kumar, Deepak Kumar, Anita Kumari This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3239769/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 In this paper, we represent icosagonal fuzzy numbers in a variety ofways, both symmetrically and asymmetrically, linearly and non-linearly as well as single valued and interval -valued. Along with this, we have alsodeveloped some defuzzification procedures with different approaches based on centroidmethod, the mean of alpha-cut method and bounded area method. In order todemonstrate the significance of these strategies, defuzzification approaches can be applied to many optimization problems in operational research. We have applied these strategies to solve the numerical example based on fuzzy assignment problem in the interview board panel with twenty parameters. This study deals with the situation where icosagonal fuzzynumbers are used to represent ambiguous information in the form of linguistic terms. The ranking function for icosagonal number is also proposed in this paper for the better comparison of two icosagonal fuzzy numbers and its primary goal is used in this research for the appropriate allocation to resolve the fuzzy assignment problem. Icosagonal fuzzy number defuzzification techniques ranking function fuzzyassignment problem. 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. 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