Real world limitations in transport optimization

When you start bringing an application based on optimization algorithms into the real world, you quickly realize that your initial model didn’t consider every situation that your clients face in their everyday business processes. Transport route optimization is one of those problems in which there are a lot of different limitations which can occur for different types of clients.

Limitations are dependent on the type of goods that the client transports, the size and type of vehicles in the client’s fleet, working hours and locations of their delivery points and the working hours of the delivery vehicles. Different outside factors, such as road conditions, traffic rules and traffic jams can also be very important in the routing process.

Your client’s entire fleet might not be able to make it to every delivery point. Delivery locations in historic parts of a city, inside shopping malls or on the end of narrow village roads can be inaccessible for larger vehicles. In those cases, it’s important to plan routes according to the limitations and to make sure that lighter vehicles are available to make those deliveries.

Another type of limitation that we have come across are pedestrian zones which have very limited times in which delivery vehicles can pass. Those deliveries have to be scheduled in a way which doesn’t significantly reduce route efficiency but also must be lenient enough to account for possible delays on the way to those points, so that we can make sure that the deliveries are successful. Due to road work or natural events such as landslides, some road sections might temporarily become closed or partially closed for some types of vehicles. All routes which go along those roads need to take these limitations into account, and resolve them either by routing smaller vehicles with permission to pass or by using alternative routes and by calculating the additional time and distance necessary to complete the deliveries.

These and many other factors are individual components in a larger routing system which bring route optimization results closer to real world expectations. Providing more information to the routing system will cause less unexpected situations during deliveries and achieve overall better customer satisfaction and results.

All the above and other restrictions depending on the needs of the clients are taken into account and set as restrictions when creating routes, while the use of the system still achieves excellent results and cost savings for clients in practice.