Using osm2po to solve Travelling Salesman Problem

Tackling the Traveling Salesman Problem with osm2po: A Real-World Guide

Ever heard of the Traveling Salesman Problem? It’s a brain-teaser that’s stumped mathematicians and computer scientists for decades. The basic idea is this: you’ve got a bunch of cities, and you need to figure out the shortest route that hits each one exactly once before looping back home. Sounds simple, right?

Well, here’s the kicker: it’s an NP-hard problem. What that really means is that as you add more cities, the computing power needed to find the absolute best route explodes. Forget about doing it by hand! But don’t worry, we don’t always need the perfect solution. Sometimes, a really good solution is good enough, and that’s where tools like osm2po come to the rescue.

Think of the TSP as more than just a salesman’s headache. It pops up all over the place! Logistics companies use it to optimize delivery routes, manufacturers use it to arrange components on a microchip, and even scientists use it for things like DNA sequencing. Anywhere you need to minimize travel or cost between multiple points, you’re basically dealing with a TSP in disguise. And trust me, the real world throws in curveballs like time windows and limited truck capacity, turning it into a whole new beast called the Vehicle Routing Problem (VRP).

So, what’s osm2po? It’s a nifty, free, and open-source tool that takes OpenStreetMap (OSM) data and turns it into a map that computers can understand for routing. I like to think of it as a translator, converting human-readable maps into machine-readable instructions. What’s cool is that it can handle massive amounts of data – entire countries, even! – without choking.

osm2po can spit out SQL files for PostGIS, making it play nice with pgRouting and QGIS. Plus, it’s got a built-in web server that can dish out routes in formats like CSV and GeoJSON. Pretty versatile, if you ask me.

Okay, let’s get down to brass tacks. How do you actually use osm2po to solve the TSP? Here’s the lowdown: