Solving large scale unconstrained optimization problems with an efficient conjugate gradient class

Solving large scale unconstrained optimization problems with an efficient conjugate gradient class | 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 Solving large scale unconstrained optimization problems with an efficient conjugate gradient class Sanaz Bojari, Mahmoud Paripour This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2563786/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 ‎The main goal of this paper is to introduce an appropriate conjugate gradient class to solve unconstrained optimization problems‎. ‎The presented class enjoys the benefits of having three free parameters‎, ‎its directions are descent and it can fulfill the Dai-Liao conjugacy condition‎. ‎Global convergence property of the new class is proved under weak-Wolfe-Powell line search technique‎. ‎Numerical efficiency of the proposed class is confirmed in two sets of experiments including 210 test problems and ten disparate conjugate gradient methods‎. 2020 MSC: 90C06, 90C30, 90C26 Optimization Large-scale problems Conjugate gradient method weak-Wolfe-Powell line search technique 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-2563786","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":176191901,"identity":"2a6ba280-19b5-4641-a3d7-9ce5a1902238","order_by":0,"name":"Sanaz Bojari","email":"","orcid":"","institution":"Hamedan University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Sanaz","middleName":"","lastName":"Bojari","suffix":""},{"id":176191902,"identity":"4a6629db-3339-4e6d-9289-d3280fa47507","order_by":1,"name":"Mahmoud 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