TSL has developed a mathematical model that designs and evaluates humanitarian missions that utilise Unmanned Aerial Vehicles. This work is featured in a new publication.
UAVs have enjoyed widespread adoption in the humanitarian sector in recent years, particularly for applications such as damage assessment and aerial monitoring. Advances in UAV designs, materials and propulsion technologies have resulted in increased range and payload capabilities, therefore paving the way for the use of UAVs in humanitarian deliveries.
However, current modelling techniques do not consider non-linear relationships that govern UAV flight. This frequently leads to an underestimation of their capabilities, and results in the use of overly conservative plans to compensate.
To address this problem, we developed a UAV-based humanitarian logistics mission design framework that incorporates tactical hub-location planning, trajectory optimisation, and operation routing. The framework contains two layers – the drone operations layer focuses on the aerodynamic properties of the UAV, while the humanitarian operations layer designs the logistical structure of the mission.
The humanitarian operations layer formulates and solves a flow assignment problem that determines the quantity of goods must be transported. Based on these results, a novel heuristic stage generates the routes, assigns cargo and vehicles to these routes, and finally ensures battery replacements are provided to support the final operational plans. This approach improves scalability, and allows its implementation on large-scale study cases.
By integrating a drone operations component into the logistics design model, the framework reduces total operation times, required battery stocks, and total energy expenditure of humanitarian missions compared to previous models.
Our papers present case studies based on the 1999 Chi-Chi Earthquake and the 2010 Haiti Earthquake, demonstrating the benefits of UAV in humanitarian response.
The techniques developed in this study have been applied to simulations large scale humanitarian response.
The model considers limited battery charge and optimises battery inventory levels and recharge processes.
Aircraft Trajectory Design
A trajectory optimisation model minimises flight time and energy consumption while considering potential obstacles.
Supply chain configuration
The output presents optimal warehouse location, battery inventory levels and transportation schemes.
Our analysis indicates that up to 54 UAV deliveries can take place at the same cost and over the same time as a single truck delivery. While trucks can support a higher cargo volumes, UAV fleets can perform deliveries in parallel and underpin a more equitable and ethical response strategy.
The framework is also applied to optimise relief operations supported by UAV real-time network damage assessment. This way, ground vehicles can travel to their destinations through safer and faster routes.