This problem came up in the real world, but I’ve translated it into a more generic “textbook-like” formulation. I suspect it is NP, but I’m particularly interested in knowing if it has a name or is well known since I think I can’t be the first one to encounter it. 😉
Imagine there is a potluck party with N guests. Each guest may bring his/her “signature dish” to the party, or bring nothing. Each guest either likes or hates each of the dishes that the other guests may bring (and this is known in advance since they are all old friends!), but they all like their own dishes.
Is there a deterministic algorithm that does not take exponential time to find the smallest set of dishes that satisfies the constraint that all guests will find at least one dish to their liking? I say “the” smallest, but actually there may be multiple solutions, and I’d like to know them all if possible.
Or, in a more abstract way, imagine a square matrix where all elements are either 0 or 1, and all diagonal elements are 1. What are the smallest sets of rows such that the sum (or the binary OR) of the rows in each set have no zeroes? (The rows would be the dishes, the columns would be the guests, 1 would mean that a guest likes a dish, and diagonal elements are 1 since everyone likes their own dish.)
This could be generalized to non-square matrices, or by removing diagonal=1 rule (although the latter guarantees that there will always be at least one solution). But I don’t care about those cases for now…
I already have a program that solves it through an exhaustive search and is fast enough for N around 20, but it takes exponential time. I’m thinking I may need to recur to stochastic algorithms to find good-enough solutions for larger values of N.
Added
Wow, thanks for the quick answer! “Set cover”, that’s the name I was looking for. 🙂
This is called the SET COVER problem and it is NP-complete.