So NP is like P again. I learned in school 13 is the max and one of my algebra professors advanced it to 15 (in the 80ies). Then came 20, then came 20.000, this is 80k with proof, and at the World TSP page we see the record was 1m. http://webhotel4.ruc.dk/~keld/research/LKH/ The biggest proven optimum is for 3178031 right now. This should be really done with CUDA, not plain C, btw.
What are you actually expecting here? The solution was found in a few days by the LKH TSP heuristic solver. They spent months (and decades of CPU time) using well-known techniques to bound the specific problem and prove that this was an optimal solution. It’s not something that you can synthesize to a page. They are literally announcing that they verified the heuristic-derived solution. Consider it like any science,…
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The proof here is essentially the execution log of the bounding program. I imagine that this would be TB, PB or beyond. Not every proof is some clever paper, some are just brute force. Like proving a number is prime, or calculating the Nth digit of Pi. A paper doesn’t always make sense, but you can still announce what you’ve done (and maybe you get a paper with algorithmic details, but it’s not a proof for specific the instance).
If you just use the simple-minded Bell Labs probabilistic algorithm, how much worse is that result? The classic TSP approach is: 1. Hook up all the nodes in some arbitrary path. 2. Cut the path in two places to create three pieces. 3. Rearrange those three pieces in the six possible ways and keep the shortest. 4. Iterate steps 2-3 until no improvement has been observed for a while. This is not guaranteed to be optima…
Iirc the (probably simplified) LKH heuristic they used:
For each iteration:
apply some randomisation
starting at each place
cut the path in 2..n places
reconnect in the most optimal way
if the new tour is the new best, save
If you just use the simple-minded Bell Labs probabilistic algorithm, how much worse is that result? The classic TSP approach is: 1. Hook up all the nodes in some arbitrary path. 2. Cut the path in two places to create three pieces. 3. Rearrange those three pieces in the six possible ways and keep the shortest. 4. Iterate steps 2-3 until no improvement has been observed for a while. This is not guaranteed to be optima…
Note that the tour itself was found quickly using a heuristic solver ( https://www.math.uwaterloo.ca/tsp/korea/computation.html ), the achievement here and all the computation is to establish that this is the lower bound (assuming I understood correctly). So, the heuristic solver worked pretty darn well :) Although, I’m not sure how close it would have been the heuristic algorithm you are describing (I suspect that i…
The algorithm that OP describes is more commonly known as 2-opt [0]. The heuristic used in this case is referred to as LKH which I assume means the Lin-Kernighan Heuristic [1]. The latter is sort of a meta generalisation of the former.
If you find this impressive, take a look at the 1.33 billion stars TSP solution provided by the same authors. - Gaia DR2 (1,331,906,450 Stars): https://www.math.uwaterloo.ca/tsp/star/gaia2.html > "The tour is at most 1.0038 times the length of a shortest-possible route."
But that presumably doesn't handle the relative motion of the stars, which makes the problem even trickier, since the distances will change as you travel, no? Or is my astronomy off base here?
It would suck to get to bar 51,248 only to find out it's now permanently closed
There was a man who documented his travel to every country in the world. Not long before he was finished, South Sudan gained independence and he had to take a special trip there to complete his journey, which apparently had already completed all the other countries in Africa long ago.