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This article is incorrect on two counts:

First of all, the travelling salesman problem is not actually about travelling salesmen; a solution has to work on an arbitrary graph, not just one that is constrained to the actual geometry of space.

Secondly, the bees' solution to the problem is heuristic; there is no guarantee they will always find the optimal solution, though they'll almost always be very close. Computers can apply heuristics too (with the same caveat), and when they do so it's much faster than verifying an algorithmic solution.



> First of all, the travelling salesman problem is not actually about travelling salesmen; a solution has to work on an arbitrary graph, not just one that is constrained to the actual geometry of space.

Not quite true, Euclidean TSP is also NP complete, so in a sense, working with real distances doesn't make the problem any easier to solve. Euclidean TSP is, however, easier to approximate, and that's really the point here: a good approximation is all that matters in practice, bees won't starve just because their solution is 0.5% worse than the optimal route.


I hope this meme won't enter the public mind like "science can't explain how bees can fly"


Yeah, the bumble-bee thing is unfortunate. But there is something to this: we can trade away a verifiably optimal solution for something more useful, like a timely one. (Coincidentally, I submitted an article on that general theme this very morning: http://news.ycombinator.com/item?id=2371977) If that concept entered the public mind it would be a great thing.

Unfortunately the article never touched on that, and all we get is "bees > supercomputers!!!".


It's not bees; it's bumblebees.

Bumblebees typically have to do warm up 'exercises'; if their flight muscles aren't warm enough, they cannot fly (http://www.bumblebee.org/bodyTempReg.htm)

Swans also are fairly close to the limits of flight; they need large stretches of water to take of, and their landings have been described as crashes.




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