Multi-Objective Trajectory and Power Optimization for UAV Relay Systems: A Pareto-Driven Approach Using Metaheuristics

Multi-Objective Trajectory and Power Optimization for UAV Relay Systems: A Pareto-Driven Approach Using Metaheuristics | 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 Multi-Objective Trajectory and Power Optimization for UAV Relay Systems: A Pareto-Driven Approach Using Metaheuristics Trang Pham, Hang Duong, Duong Dinh Trieu, Vu Trinh Anh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9300384/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract This paper addresses the joint trajectory and power optimization problem for UAV-assisted amplify-and-forward (AF) relay systems under probabilis-tic LoS/NLoS channels. A max–min throughput formulation is adopted to ensure fairness among multiple ground users while capturing the trade-off between system efficiency and quality-of-service (QoS). To solve the resulting high-dimensional non-convex problem, we propose an efficient metaheuristic framework based on the Chernobyl Disaster Optimizer (CDO), which avoids complex convex approximations required by conventional methods. Simulation results show that the proposed approach consistently outperforms benchmark algorithms, including PSO, BA, and SCA, while maintaining a stable and high minimum rate as user density increases. Furthermore, Pareto-front and statistical analyses confirm the robustness and reliability of the proposed method in realistic urban deployment scenarios. UAV max–min fairness throughput metaheuristic optimization trajectory Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 17 May, 2026 Reviews received at journal 11 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers invited by journal 05 May, 2026 Editor assigned by journal 30 Apr, 2026 Submission checks completed at journal 03 Apr, 2026 First submitted to journal 02 Apr, 2026 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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