Route optimization

Route optimization is when a computer figures out the sequence and method that will cost the least time and money when moving between multiple delivery points or stops. It's similar to mentally working out which store to visit first to save steps when running several errands at once, but when a person has to do this math for dozens of orders and hundreds of couriers, it takes a long time and mistakes creep in.

Bringing AI into the picture changes things. An AI trained on historical delivery records can instantly judge, for each incoming order, which delivery method and route will be cheapest and fastest. What sets it apart from older approaches is that it factors in constantly shifting conditions like road conditions or courier locations, finding the best option on the fly instead of looking up a pre-set rule table.

In articles, this shows up in phrasing like "route calculation time dropped from 20 minutes to 2 minutes 30 seconds." It's easy to misunderstand, but this isn't the same as a map app's navigation feature. Rather than simply finding the shortest distance, it refers to a comprehensive judgment that includes which carrier, which delivery method, and even which timing to choose.

Try telling a chatbot five or six places you need to visit today along with the travel time between each, and ask it to "arrange the most efficient order to visit these." This lets you experience a small-scale version of route optimization firsthand.