[kaba0]

> Trained Humans are surprisingly good at these problems

Are we? I don’t think we would even start working on problems with big enough `n` where the complexity actually ramps up.

Like, optimally scheduling even just a couple of things will have a shitton of combinations, and I really doubt we would be good at it.

Good at iteratively decreasing a cost function? Yeah, I guess with a good interface we could move around tasks to be scheduled on a timeline and optimize it. Finding the optimum? No chance.

[hinkley]

Our monkey brains can get within a few % of optimal on written TSP problems.

For a lot of these problems, having a tight upper bound lets you narrow the search space, regardless of whether you're looking for the ideal answer or simply a less-bad one (Would you turn down saving $500,000 on fuel and labor in a year just because someone thinks $613,000 is the maximum savings achievable?)

The more we can get automation to do approximations as well as humans, the better.