Trucking is a trillion dollar industry. Most, if not all products travel by trucks at one stage or another in their supply chain. These trucks are usually being managed by third-party logistics companies that don't own the cargo nor the vehicles. The main function of these companies is to match the jobs to the vehicles. To a large extent, their profit margin depends on the efficiency of that matching. Efficiency can be achieved by formulating the matching problem as an optimization problem and then solving it every time a new job arrives. The same problem is being solved daily by food delivery services like Foodora, DoorDash and "taxis" such as Uber and Lyft.

The video below is showing a simulation of a transportation fleet that regularly receives new pickup and delivery jobs. PS. If anyone can recommend a free/cheap Python package capable of finding driving route and visualizing the polylines on a road network, then I'd be grateful.