A mathematical model for the design of humanitarian response missions that utilise Unmanned Aerial Vehicles has been developed by TSL, and is the subject of 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.
Current modelling techniques do not consider non-linear relationships that govern UAV flight, resulting in an underestimation of their capabilities and overly conservative plans. We address this gap by developing a UAV-based humanitarian logistics mission design framework that incorporates tactical hub-location planning, trajectory optimisation, and operation routing.
The framework can be applied to determine optimal UAV-based humanitarian response operations. 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.
2. Energy Management
The model considers limited battery charge and optimises battery inventory levels and recharge processes.
3. Aircraft Trajectory Design
A trajectory optimisation model minimises flight time and energy consumption while considering potential obstacles.
4. Supply chain configuration
The output presents optimal warehouse location, battery inventory levels and transportation schemes.
Results of our optimisation show that based on conservative estimations of delivery times and UAV costs, 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 delivery bulk, 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. Our analysis indicates that significant reductions in mission time are achievable through this approach.