# Unmanned Aerial Vehicle Routing Problems: A Literature Review
## 5 Challenges in UAV Routing
### Fuel Consumption and Range  
From the airline industry we know that the fuel/energy consumption depends on certain factors such as maximum flight distance or the flight time of the UAV could be constrained by gross takeoff weight, empty weight, thrust to weight ratio [PERSON] et al. (2016), fuel weight, payload, and number of battery units [PERSON] et al. (2016), thereby giving more emphasis to the criticality of focusing on fuel consumption.  
The range of the UAV is also a crucial aspect where the existing literature has not to give attention and the range is not the same as fuel consumption, as the extent of this depends on many other conditions. How far an UAV can travel is described as range, and the range of a UAV is dependent on the amount of energy capacity of the UAV, endurance, flight speed, and aerodynamic performance [PERSON] et al. (2016); [PERSON] et al. (2016). Endurance for an UAV can be explained at the total time taken during flight. For an electric fixed-wing aircraft or quadrotor, this is directly related to the capacity of the battery and the amount of current the motor produces to keep the aircraft in the air. There are many other aircraft parameters that determine the endurance for any UAV; however, the range of the UAV heavily depends on UAV dimensions, Weight, and Payload [PERSON] et al. (2016); [PERSON] et al. (2016). Any entity that is concerned about UAV security should be extremely concerned about the endurance and range capabilities of various types of UAV categories.  
In routing algorithms, some studies have either assumed unlimited fuel capacities [PERSON] et al. (2016) in UAV routing or not considered the fuel at all in their approaches to solving UAV routing. Certain studies in UAV routing have considered fuel as a constraint [PERSON] et al. (2016); [PERSON] et al. (2016), and [PERSON] et al. (2014) introduce a fuel-constrained UAV routing problem (FCURP). This implies that, given a set of targets and depots and a UAV that is initially stationed at one of the depots, a path can be found for the UAV such that each target is visited at least once, the fuel constraint is never violated along the path for the UAV, and the travel cost for the vehicle is a minimum.  
Although fuel consumption is typically considered in vessel routing [PERSON] et al. (2016), when it comes to UAVs, the fuel consumption models differ from vessels by depending on not only just speed but also weight or type of payload and weather conditions [PERSON] et al. (2016). For vessels, the non-linear aspects are heavily dependent on the speed of the vessel [PERSON] et al. (2016). Even though existing research uses linear approximations [PERSON] et al. (2016), we know from industry that this is not a reasonable approach for UAVs where the weight of the payload is more critical when seen in combination with speed and weather conditions [PERSON] et al. (2016); [PERSON] et al. (2016); [PERSON] et al. (2016). From the airline industry, one can find comparable models for flight--such as available fuel models for multirotor helicopters [PERSON] et al. (2016)--that indicate that linear approximation of the energy consumption is not applicable for large variations of the payload carried [PERSON] et al. (2016).