Optimizing Runway Orientation: A Fine-Scanning Algorithm and Continuous Area Integration Approach

Received: 22 January 2026 | Revised: 28 February 2026 and 15 March 2026 | Accepted: 24 March 2026 | Online: 14 April 2026

Corresponding author: Trong Hiep Nguyen

Abstract

Optimal runway orientation is a determinant of airport operational safety and capacity, governed by the requirement to maximize the Usability Factor (UF) under adverse crosswind conditions. Traditional planning methodologies, specifically the graphical wind rose technique and some computational models, often rely on coarse 10-degree increments or linear approximations. This approach may induce a "precision gap" that fails to capture the true mathematical optimum when processing grouped meteorological data. This study introduces V-ROpt, a high-precision automated framework that utilizes Continuous Area Integration (CAI) logic to resolve the partial coverage problem within 16-direction wind sectors. By implementing an exhaustive fine-scanning algorithm at 0.5-degree resolution, the framework minimizes discretization error inherent in conventional techniques. The numerical results demonstrate that V-ROpt can identify a localized optimum representing a 1.0-degree shift from traditional 10-degree methods, achieving a marginal usability improvement of 0.03%. For complex airfield configurations, where a single runway fails to meet the required 95% UF, the proposed framework generates a portfolio of the top 5 optimal crosswind runway scenarios. The computational results demonstrate that the proposed crosswind runway orientations improved the combined UF by 6.38%-7.76% compared to the single-runway configuration, which initially provided a UF of only 91.08%. This enables planners to perform trade-off analyses between aerodynamic efficiency and physical constraints, such as terrain, obstacle limitation surfaces, or other environmental constraints.