The Wikipedia article on Logistics states that Logistics is the management of the flow of things between the point of origin and the point of consumption to meet the requirements of customers and corporations. Logistics is something that many industries like e-commerce, shipping companies, fast food, etc. need to deal with.
Companies can use graphs to represent shipping networks where nodes are distribution hubs or branches and the edges are delivery routes. We can then use Dijkstra’s algorithm on the graph to determine the shortest path from one point to another.
In Logistics, there are many variables that the nodes and edges can have. Specific distribution hubs or routes might have certain properties like cost, availability, carbon footprint, time, etc. that we must also take into account. Property Graphs can be used to attach properties to nodes or edges.
Then Dijkstra’s algorithm can give us the shortest available path that can minimize many things like cost and carbon footprint also taking into account things like what we are transporting.
Something that I didn’t think about that is discussed in the article I read was the computation time taken to find the shortest path. Property Graphs solve this computation problem and this is why they are used instead of regular Graphs as they take node and edge properties into account during computation rather than after.
Source: https://dev.to/fppt/managing-delivery-networks-a-use-case-for-graph-databases-2jb0