Strategic Framework for Future Adaptive Hybrid RPAS Models in Swarm Logistics

This study introduces a multi-objective optimization model for RPAS logistics, aiming to minimize energy consumption, delivery time, and safety risks. The framework is developed based on the SORA methodology, incorporating air risk class and ground risk class metrics to ensure a comprehensive safety evaluation. The optimization problem is solved using NSGA-II, which explores the trade-offs between these competing objectives. The study evaluates three delivery schemes, referred to as Optimum, Highways, and Hybrid. The Optimum scheme maximizes efficiency by allowing RPASs to take direct routes, significantly reducing travel distances and energy consumption. The Highways scheme restricts RPAS to designated air corridors, enhancing safety and regulatory compliance but resulting in longer travel distances. The Hybrid scheme dynamically adapts routes by combining the flexibility of the Optimum approach with the structured nature of the Highways scheme, aiming to balance efficiency and safety under mixed operational conditions. Key findings indicate that the Optimum scheme achieves the lowest energy consumption and travel time, while the Hybrid scheme offers a balanced approach that mitigates safety risks without severely impacting efficiency. These insights support logistics providers and policymakers in choosing RPAS delivery strategies that align with operational needs and regulatory requirements.