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Thankfully, the Google Maps API makes this information freely available, so all it took was a short Python script to calculate the distance and time driven for all 2,450 routes between the 50 landmarks.Now with the 2,450 landmark-landmark distances, our next step was to approach the task as a traveling salesman problem: We needed to order the list of landmarks such that the total distance traveled between them is as small as possible if we visited them in order.
You may note that cities from North Dakota, Vermont, and West Virginia are missing.Last week, Tracy Staedter from Discovery News proposed an interesting idea to me: Why not use the same algorithm from my Where’s Waldo article to compute the optimal road trip across every state in the U. The result was an epic itinerary with a mix of inner city exploration, must-see historical sites, and beautiful natural landscapes. One of the hardest parts of planning a road trip is deciding where to stop along the way. To stand a chance at making an interesting road trip, Tracy and I laid out a few rules from the beginning: With those objectives in mind, Tracy compiled a list of 50 major U. landmarks — one in each state excluding Alaska/Hawaii and including D. Tracy wrote about that process on Discovery News here.I hope this article convinced you that machine learning can play a crucial role in that planning phase and save you a ton of time along the way.Of course, it may not be practical for you to take a road trip of epic proportions like the ones described here.
Out of the top 400 recommended cities to visit on Trip Advisor, none were from North Dakota, Vermont, nor West Virginia.