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> these problems are commonly in the class NP "Is the input empty" is in the class NP. You mean these problems are NP-complete. (This means "In NP, and all oth

> these problems are commonly in the class NP "Is the input empty" is in the class NP. You mean these problems are NP-complete. (This means "In NP, and all other problems in NP can be reduced to them in polynomial time.") > If practical problems in combinatorial optimization are of interest, then bring them forward -- they've been coming forward mostly only rarely. This is total nonsense. Training a neural network is combinatorial optimisation, proving mathematical theorems is NP-complete (when max proof-length is specified in unary), and there are loads of integer programs running all over the place that we'd love to solve significantly faster. Sure, maybe you don't always need to get to optimality, but every bit helps, and often approximate methods just aren't good enough. (As the sibling comment points out, though, none of this is really germane to a discussion of quantum computers.)

graycat 8y ago
Sorry about saying NP instead of NP-complete -- I've been doing other things for a long time and typed too quickly. > there are loads of integer programs running all over the place that we'd love to solve significantly faster. Some years ago I had a good background in optimization including integer programming and had some successes. But slowly I had to conclude that actually the world had decided that such optimization was just not worth the bother. So, I never saw "loads". Once I talked to a guy, and we considered airline scheduling (I got started in that when I was Director of Operations Research at FedEx). His remark was that optimization was no good because the schedules it gave were "too tight". That's like a kid who likes chocolate cake saying that he doesn't want to eat any of his orange flavored birthday cake because it is too big. Having the optimization put, say, five minutes of slack at each stop in the schedule is the easiest thing in the subject. Mostly people in business just do NOT want anything technical they don't understand. So, as soon as mention, say, Lagrangian relaxation, they want nothing to do with integer programming. Or if such a project flops, then they have a failure on their record. If the project is successful, maybe the integer programming guy is a threat.
- repsilat 8y ago
  Thanks for writing back, sorry if my tone wasn't great before. > optimization was no good because the schedules it gave were "too tight". This matches fairly well with my experience -- getting a good objective function can be half the battle. A lot of people don't know what they want well enough to tell you. > Mostly people in business just do NOT want anything technical Well, in competitive markets it'll eventually be "do or die", and for common enough problems it doesn't need to be done in-house. I agree that businesses are (typically) very conservative about this sort of thing, but if there's value to be had by wringing efficiencies out of operations, Uber and Amazon will do it.

graycat 8y ago

Sorry about saying NP instead of NP-complete -- I've been doing other things for a long time and typed too quickly. > there are loads of integer programs running all over the place that we'd love to solve significantly faster. Some years ago I had a good background in optimization including integer programming and had some successes. But slowly I had to conclude that actually the world had decided that such optimization was just not worth the bother. So, I never saw "loads". Once I talked to a guy, and we considered airline scheduling (I got started in that when I was Director of Operations Research at FedEx). His remark was that optimization was no good because the schedules it gave were "too tight". That's like a kid who likes chocolate cake saying that he doesn't want to eat any of his orange flavored birthday cake because it is too big. Having the optimization put, say, five minutes of slack at each stop in the schedule is the easiest thing in the subject. Mostly people in business just do NOT want anything technical they don't understand. So, as soon as mention, say, Lagrangian relaxation, they want nothing to do with integer programming. Or if such a project flops, then they have a failure on their record. If the project is successful, maybe the integer programming guy is a threat.

repsilat 8y ago
Thanks for writing back, sorry if my tone wasn't great before. > optimization was no good because the schedules it gave were "too tight". This matches fairly well with my experience -- getting a good objective function can be half the battle. A lot of people don't know what they want well enough to tell you. > Mostly people in business just do NOT want anything technical Well, in competitive markets it'll eventually be "do or die", and for common enough problems it doesn't need to be done in-house. I agree that businesses are (typically) very conservative about this sort of thing, but if there's value to be had by wringing efficiencies out of operations, Uber and Amazon will do it.