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I currently use a web API to solve TSP tasks. However my provider limits the query to a maximum of 150 stops. I therefore consider to host my own routing service based on OSM data and pgrouting. My top priority is performance and I was wondering if anybody has experience with the performance of the pgr_tsp function? I don't care about exact stats or system specs. All I want is a ballpark figure in order to see if pgrouting is an option at all.

E.g. Can I calculate TSP for 1000+ stops and is this a matter of seconds or hours?

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  • To give you an idea (not pgrouting based but our RW Net 4 software): With 1000 stops we recommend appr. 50 sec of calculation to get a decent solution. With multiple threads or if you accept a not so good solution, it can be faster. In any case you will also need a cost-matrix between the 1000 stops and here calculation time depend a lot upon distance between stops and level of details in the network. – Uffe Kousgaard Jan 30 '16 at 9:51
  • @UffeKousgaard Thanks for the reply. Calculating the actual network distance matrix for 1000 stops (i.e. ~1.000.000 routes), seems impractical. I read that using euclidean distance is often sufficient to get a near optimal solution. How do you get your distance matrix? Do you actually calculate all shortest paths? – Chris Jan 30 '16 at 10:15
  • Yes, using euclidean distance is a joke IMHO, if you are going to use the result for anything serious. Calculations are done as 1000 one-to-many, rather than 1,000,000 one-to-one. – Uffe Kousgaard Jan 30 '16 at 10:43
  • Real cities has oneway streets, rivers, railways and many other obstacles, which prevent straight lines when moving from one stop to another. – Uffe Kousgaard Jan 30 '16 at 10:50
  • @UffeKousgaard Yes, I read that in the postgreSQL pgrouting docs and that's how they implemented their tsp algorithms default behaviour. However, I also realized that it does not really work for small areas. I.e. stops are distributed on a street level rather than spread across multiple cities. The euclidean only seems to work well for long distance TSP. I assume this is because the street network becomes sufficiently dense when you zoom out and the euclidean distance converges with the actual driving distance. – Chris Jan 30 '16 at 10:59
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Complementing, previous answer.. montevideo-release-v4 is the latest branch. There is a lot of clean up that needs to be done as everything we coded is still there even if its not used.

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The authors of "Fast data-oriented microaggregation algorithm for large numerical datasets" [1] proposed a TSP solution for millions of cities in Euclidean space. Their solution is fast enough for your application and is based on Clark-Wright heuristic.

[1] http://www.sciencedirect.com/science/article/pii/S0950705114001956

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