Please see the attached files for additional information regarding this assignment.

Assumptionsof the Logistical Model
Comment by Jeremy Hodges: I thought you were comparing mishap accident rates of UAVs and manned aircraft.
Is this model already developed? It does not seem feasible.

Writer read the “Objective”, this information doesn’t make sense.

We need to re-write this portion to meet what the professor is asking in his feedback. We need to compare mishap accident rates of UAVs & manned aircraft.!!!!!

The first assumption is that distribution centers can be used to serve different demand points for humanitarian aid while the opposite is not allowed (Gomez & Purdie, 2017). This is a basic assumption in transportation networks where flows start from distribution centers to multiple destinations without allowing the vice versa from occurring. In disasters, this assumption is even more necessary so that humanitarian aid can be supplied from a distribution center to multiple areas where it is needed.

The second assumption is that demand for humanitarian aid from each distribution center will be modeled as a Poisson process since it is generated by the demand from the service areas where the services are needed (Malandrino et al., 2019).

The third assumption is the demand for humanitarian aid per a given unit of time will also be modeled as Poisson processes and will not only be independent but also identically distributed with a given rate. It should be noted that the second and third assumptions complement each other. Different literature predominantly uses the Poisson process to model demand which informs this study’s choice to use a similar modeling framework (Gomez & Purdie, 2017).

The fourth assumption is that shipments between distribution centers are not allowed in the model. Equally, shipment between demand points is also not allowed (Malandrino et al., 2019). This is because such shipments are impractical in real-world settings. Although such shipments are common in conventional supply chains, they cannot be employed in the supply of humanitarian aid as their possibilities are very limited, hence the decision to leave them out in most humanitarian logistic literature (Malandrino et al., 2019).

The fifth assumption is that the Euclidean distance will be used to measure the distance between the distribution center for humanitarian aid and the demand points where the aid is needed. In an area where there is a sparse logistics network, the Euclidean distance will be multiplied with a factor to ensure that the travel distances used are realistic (Malandrino et al., 2019). This distance is important given that mishaps are seen to increase with distance that is travelled during delivery.

The sixth assumption is that the shape used to model the service regions will have a circular shape. Different articles agree that the shapes used to model the logistics service regions have no effect on the optimal solution. In addition to that, the distribution center for humanitarian aid is assumed to be centrally placed in the service areas (Gomez & Purdie, 2017). Given this, it can be easy to determine the average distance between the distribution center and the demand points.

There are other assumptions that are disaster specific. One such assumption is that sufficient Northrop Grumman MQ-8B Fire Scout drones, as well as disaster manned systems, are available at any given point in time. Another assumption is that the limitation of facilities in terms of capacities is ignored (Malandrino et al., 2019). As well, the UAVs are assumed to always carry loads at full capacity at any given point in time.

Developing the Model

To develop the model that will replicate the mishap rates to establish the effectiveness of the use of UAVs in disaster-stricken areas, several guidelines will be followed. The logistics network will be expressed in the form of smooth continuous functions. The logistics network will be represented in a two-dimensional space with demand points represented by discrete points within the service area in the two-dimensional space (Gomez & Purdie, 2017). The demand for humanitarian aid in the demand points will be modelled as Poisson processes.

The model will incorporate the rates mishaps for both UAVs and manned systems in different types of disasters and landscapes. More specifically, the two modes of delivery will be compared in terms of mishap rates in mountainous landscapes, shrub lands, coasts and wetlands. The rates that are encountered in such disasters as hurricanes, tsunamis, fires and earthquakes will also be integrated in the model to ensure that it depicts the real world mishaps rates. Writer where is this information (data) that supports this issue as per the feedback from the professor? Comment by Jeremy Hodges: Ok. Comment by Jeremy Hodges: Ok…do you have access to this data already? If so, I recommend you simply conduct a t-test for independent means comparing this accident rates…hypothesis that the UAVs will have lower accident rate…null hypothesis that UAVs and manned rates are the same.
I do not think the development of this model is something viable that you can accomplish in the next couple of weeks, based on this proposal.

Another feedback from the professor:

Do you have the ability to create and execute this model in order to derive the data needed for your t test?
If you have the ability to create and execute this mathematical model in order to derive the data needed for the t test, revise your paper in what I asking you.