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Ask HN: P=NP, what do you do?

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Ask HN: P=NP, what do you do?

#1
Imagine you are a reclusive scientist genius who after spending the last 15 years exploring the space of algorithms for solving 3SAT, has stumbled upon a fast polynomial-time solution.

Somewhat tired as you are of the academic community, and not very interested in prizes or distinctions, you decide it would be in your best interest to try to monetize your discovery privately. To this purpose, what massively lucrative applications can you think of for such an algorithm?

Re: Ask HN: P=NP, what do you do?

#3
let people make a shopping list, then give them the best deal there is on all the things combined, with as few shipments and registrations as possible, maybe let them pick how many max new stores, and let them keep a list of stores they like -- and once you've made a bunch off that, announce how you did it, claim the million dollar prize and tada - the first mathematician i'm aware of who didn't care about the world's ridiculousness, yet wanted to cash in.

if you really want to give a finger to the academia though, just publish it - and include a long essay on all the various ways the academic institutions hindered your progress, how bureaucratic they are, and how little they actually care about advancing knowledge. further, publish it on a blog instead of an academic journal, ask for peer review, and don't mention your university once anywhere on the blog. that'll show 'em, those punks.

Re: Ask HN: P=NP, what do you do?

#4
If you have an algorithm with a worst case polynomial bound on the time it takes to solve an NP complete problem, then UPS, Fedex and other companies would pay nicely to use a service to optimally do scheduling, routing and resource allocation.

On the other hand, since it is more likely that P!=NP, this "almost" algorithm probably fails exponentially on some set of examples, and in practice there are plenty of NP complete problems which enjoy very good approximation algorithms or heuristic algorithms which work well for typical problem instances.

Re: Ask HN: P=NP, what do you do?

#5
Bid the spy agencies against each other. Make sure you tell the Americans that you are really working for them so they don't kill you and they also protect you from all the other people that want to kill you.

Edit: Who I am kidding, the Americans would not want the other countries to know P=NP and talking to anyone else would be grounds for disappearance. So there would be no bidding war, you'd have to take what you can get from the NSA/CIA. Anything less than 1M a year for life would be insulting and they know that.

Re: Ask HN: P=NP, what do you do?

#6
You can break a lot of crypto - so if illegality is your speciality, you can break whatever you want. If you want to remain legal, there are plenty of bidders who will pay for epoxyed black boxes that will do decryption.

There's also the UPS/Fedex route - which isn't worth as much money, but you could sell them a black box that does fast routing for money.

Re: Ask HN: P=NP, what do you do?

#7

If you have an algorithm with a worst case polynomial bound on the time it takes to solve an NP complete problem, then UPS, Fedex and other companies would pay nicely to use a service to optimally do scheduling, routing and resource allocation. On the other hand, since it is more likely that P!=NP, this "almost" algorithm probably fails exponentially on some set of examples, and in practice there are plenty of NP com…

and if you in fact have a problem that shows P=NP, publish it so you can win the millenium prize, 1 million dollars plus ease at getting tenure so you can goof off is nothing to sneeze at

Re: Ask HN: P=NP, what do you do?

#9
almost is very far from done. If you have REALLY done it then probably somebody else might do it as well in the (not so) near future.

Also, what is the degree of the polynomial solution? If it is high then fast approximate solution might be preferable to exact slower solution (example: Simplex vs. Ellipsoid algorithms for LP) . If the solution is not linear or quadratic the most this hugely decreases your potential market.

If I am at such position I would look at problems for which I can beat precision/time for approximate algorithms.

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