A Novel Framework for Prioritizing Road Construction Projects via Clustering-Based Optimization of Resource Allocation

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This preprint studies a structured decision-support approach for prioritizing road construction projects under fiscal constraints, using a data collection protocol to define four parameters aligned with regulatory and engineering standards. The authors analyze 300 candidate projects, employing an unsupervised clustering method combined with a Charged System Search (CSS) optimization framework to assign projects to three priority tiers with weights of 0.94, 0.49, and 0.40, and to derive four budgeting strategies spanning 8 to 300 projects. Prioritization is driven by travel demand, socioeconomic benefits, cost efficiency, and environmental impact. A stated caveat is that the work is a preprint that has not been peer reviewed by a journal. 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

Abstract Expanding road transport infrastructure remains a strategic priority in many developing nations, particularly those with rising geopolitical relevance. In contexts where fiscal resources are constrained and competing stakeholder interests complicate decision-making, a structured prioritization approach becomes essential. This study identifies four core parameters influencing road design and construction, ensuring alignment with regulatory and engineering standards. A rigorous data collection protocol was implemented, and the resulting quantitative analyses informed the development of a novel decision-support framework grounded in the Charged System Search (CSS) algorithm. Utilizing an unsupervised clustering method, 300 candidate projects were classified into three priority tiers, with assigned weights of 0.94 (Priority 1), 0.49 (Priority 2), and 0.40 (Priority 3). These clusters guided the formulation of four distinct budgeting strategies, each accommodating between 8 and 300 projects. Prioritization was driven by four key variables: travel demand, socioeconomic benefits, cost efficiency, and environmental impact. The proposed model provides national infrastructure authorities with a data-driven framework for managing complex transport development portfolios, enhancing both transparency and strategic coherence.
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A Novel Framework for Prioritizing Road Construction Projects via Clustering-Based Optimization of Resource Allocation | 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 Novel Framework for Prioritizing Road Construction Projects via Clustering-Based Optimization of Resource Allocation Ramin Vafaei Poursorkhabi, Eshagh Rasouli Sarabi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7743554/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 Expanding road transport infrastructure remains a strategic priority in many developing nations, particularly those with rising geopolitical relevance. In contexts where fiscal resources are constrained and competing stakeholder interests complicate decision-making, a structured prioritization approach becomes essential. This study identifies four core parameters influencing road design and construction, ensuring alignment with regulatory and engineering standards. A rigorous data collection protocol was implemented, and the resulting quantitative analyses informed the development of a novel decision-support framework grounded in the Charged System Search (CSS) algorithm. Utilizing an unsupervised clustering method, 300 candidate projects were classified into three priority tiers, with assigned weights of 0.94 (Priority 1), 0.49 (Priority 2), and 0.40 (Priority 3). These clusters guided the formulation of four distinct budgeting strategies, each accommodating between 8 and 300 projects. Prioritization was driven by four key variables: travel demand, socioeconomic benefits, cost efficiency, and environmental impact. The proposed model provides national infrastructure authorities with a data-driven framework for managing complex transport development portfolios, enhancing both transparency and strategic coherence. Transport infrastructure prioritization Charged System Search clustering resource allocation decision support 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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