Drone Applications for Logistics and Disaster Management

Source: Warehouses with Brains

Unmanned Aerial vehicles (UAVs), commonly known as a drone, have been used recently to distribute products by different companies, such as Amazon for small packages and DHL for medical supplies to a car-free island off the coast of Germany.

There are several reasons to use drones:

  1. The delivery area may not be accessible by land and only delivery from air is possible. This case may happen specifically in disasters such as flood.
  2. Trucks can be used efficiently to distribute products to customers with larger demand size and delivery to smaller demand size can be done by drones.
  3. Drones’ pathways are not limited to roads and streets and they are able to fly directly to destinations. They also do not get stuck in traffic jam. So, delivery time can be reduced by using drones.
  4. Since fly time/distance of drones is limited, trucks can serve as the carriers of drones. When the truck is close enough to the customer, they will dispatch the drones for final delivery to take advantage of drones’ faster speed and overcome battery problems. This type of delivery also contributes to green energy due to the fact that less fossil fuel is used.

Logistics

The applications of drones for faster delivery of products and services are fairly new and there are great deals of room for improvement. This includes several problems related to routing, allocation, location, and many more problems. The research considers several advantages including faster speed and direct fly, as well as some limitations of these kinds of vehicles such as travel distance, capacity limit, aviation regulations, and more. Currently, Patchara Kitjacharoenchai is working on the routing problem using multiple trucks and drones to make deliveries. He propose the new routing model called Multiple Traveling Salesman Problem with Drones (mTSPD), in which a drone is launched from atop one of trucks, autonomously delivers a package, and then returns to the truck while the trucks are making deliveries simultaneously. The trucks can make deliveries to many customers on the tour while the drone can deliver the package to a specific customer at the faster speed without having to get stuck on traffic and can travel across the river or harsh terrain quite easily. Examples of the solution routes obtained from mTSPD model can be seen in two case studies presented here. The following site provides the generated instances to test the mTSPD: https://github.com/pkitjach/Drone-Problem-Sets.

Disaster Management

Unmanned Aerial Vehicles (UAV) or drones have widely been used in humanitarian operations because of their accessibility to inapproachable areas for ground vehicles. Furthermore, compared to ground vehicles, UAVs are versatile for collecting data, monitoring, and airlifting relief goods. Unlike satellites, UAVs can capture aerial imagery at a far higher resolution, more quickly and at much lower cost. These characteristics of UAV provide a lot of opportunities for operations in disaster management.

For example, several lightweight UAVs were launched in the Philippines after Typhoon Haiyan in 2013 and Haiti after Hurricane Sandy in 2012. UAVs also were flown in response to the massive flooding in the Balkans and after the earthquake in China in 2014. To promote the safe and responsible use of UAVs in humanitarian settings, UN groups such as the Office for the Coordination of Humanitarian Affairs (OCHA) joined Humanitarian UAV Network (UAViators).

Drones with a moving station

MovingStation

The moving station is presented as a means to solve various issues of current drone delivery problems. Currently, the challenging issue of drones delivery is limited loadable capacity and flying distance. The moving station acts as a loading and charging station for drones to address these limitations and take full advantage of drones delivery that provides timely and inexpensive service for a wide range of operation field. This problem presents a new problem with the vehicle routing of multiple drones and the multi-period allocation of the moving station.

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