A Novel Self-Adaptive, Non-Metaphor-Based FISANET Framework for Pressure Dependent Optimization of Water Distribution Networks

A Novel Self-Adaptive, Non-Metaphor-Based FISANET Framework for Pressure Dependent Optimization of Water Distribution Networks | 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 Self-Adaptive, Non-Metaphor-Based FISANET Framework for Pressure Dependent Optimization of Water Distribution Networks Vishal Jain, Ruchi Khare This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7492832/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Water Resources Management → Version 1 posted 5 You are reading this latest preprint version Abstract Water distribution networks (WDNs) are a critical infrastructure that connects sources of water to end consumers, where cost optimization remains a fundamental challenge due to substantial construction investments required. This research introduces FISANET, a novel self-adapted, metaphor free optimization approach for cost-effective water distribution network design. This FISANET approach is developed in a Python environment with integration in EPANET 2.2 hydraulic solver, which eliminates the need for complex parameter tuning while maintaining computational efficiency. Performance evaluation is being conducted on three established benchmark networks, namely the Two-Loop Network (TLN), the Hanoi Network (HN), and the New York Tunnel (NYTN) Network, along with a real-world field water distribution network of the School of Planning and Architecture (SPAN), Bhopal, M.P., India. Results demonstrate that FISANET achieves optimized cost solutions with significantly reduced function evaluations compared to other existing approaches. Also, this pressure-driven demand analysis (PDD) integrated FISANET approach consistently outperformed traditional demand-driven Analysis (DDA) approaches, achieving a cost reduction to 1.62% and found new best solution for the New York tunnel network, while also achieving best-known solutions for Two-loop and Hanoi networks. The self-adaptive nature of FISANET requires less computational costs associated with algorithm calibration, making it particularly suitable for practical engineering applications where rapid convergence and reliability are essential for infrastructure design decisions. Water Distribution Network FISANET Optimization Algorithms Pressure Driven Analysis Full Text Cite Share Download PDF Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Water Resources Management → Version 1 posted Editorial decision: Major revisions 05 Nov, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers invited by journal 29 Sep, 2025 Editor assigned by journal 31 Aug, 2025 First submitted to journal 30 Aug, 2025 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. 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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-7492832","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":522105883,"identity":"e3718f28-e86f-4731-8a8f-ce01f4e5d3af","order_by":0,"name":"Vishal 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