AeroEP: A Logistics Route Planning Tool for Rotary-Wing Aircraft

Resumen

Currently, modernizing logistical processes in the Armed Forces is essential to achieve efficient, sustainable, and adaptable operations in complex scenarios. In the Peruvian Army, helicopter supply route planning is hindered by manual methods, lack of intelligent tools, and limited resources, reducing response capacity and operational effectiveness. The core problem is the need to optimize route planning in environments with diverse supplies and dynamic conditions, where traditional methods fail to ensure efficient use of time, distance, and fuel. The absence of an integrated system further limits strategic decision-making and resource utilization. To address this challenge, AeroEP was developed—a web-based machine learning tool for optimizing helicopter routes in the Peruvian Army. Developed using the SCRUM agile methodology, AeroEP follows three phases: planning, design and development, and testing. The system incorporates a 2-opt route optimization algorithm that considers distance, flight time, and fuel consumption, enabling efficient simulation and reorganization of routes. Its modular design and interactive web interface allow real-time data integration and availability for operational decision-making. Simulation results show that AeroEP significantly enhances operational efficiency: total distance traveled decreased by 13.98%, flight time by 13.55%, and fuel consumption by 13.97%, achieving an average efficiency improvement of 13.84%. The tool optimized routes in only 0.1658 seconds, demonstrating its suitability for dynamic and resource-constrained environments. These findings confirm AeroEP’s effectiveness as a decision-support system for logistical planning, supporting institutional modernization, optimal resource utilization, and improved operational resilience in the Peruvian Army.