Some background: I'm writing a more or less brute force search algorithm for solving a problem that I have. In order to do this, I need to generate and evaluate all possibilities to find out which is best. Since the evaluation actually takes some time I would prefer to generate as little as possible solutions that completely cover my search space. Furthermore, the more elements I can do this for, the better. For any number K there are normally K! permutations, and generating them all will be hard for numbers higher than ~10.
Real problem: The search space should contain all permutations of two elements (N times el1 and M times el2, where K=M+N), with these restrictions:
- they have to be unique (i.e. I only want [a a b b b] once)
- I don't need the reverse of any permutation (i.e. if I have [a a b], I don't also need [b a a])
- I consider the permutations to be circular, so [a a b] = [a b a] = [b a a]
If I would be able to do this, the number of possibilities would be decreased drastically. Since K will ideally be large, it is not feasible to first generate all permutations and then filter them according to these criteria. I have already done the first restriction (see below) and it cut back the number from 2^K for Matlab's normal permutations function (perms) to K!/N!M!, which is a huge win. The second restriction will only cut the number of possiblities in half (in the best case), but I think the third should also be able to really cut down the number of possibilities.
If anyone knows how to do it, and preferably also how to calculate how many possibilities there will be, that would help me a lot! I would prefer an explanation, but code is also fine (I can read C-like languages, Java(Script), Python, Ruby, Lisp/Scheme).
For the interested: Here is the algorithm for getting only unique permutations that I have so far:
function genPossibilities(n, m, e1, e2)
if n == 0
return array of m e2's
else
possibilities = genPossibilities(n-1, m, e1, e2)
for every possibility:
gain = number of new possibilities we'll get for this smaller possibility*
for i in max(0,(m+n-gain))
if possibility(i) is not e1
add possiblity with e1 inserted in position i
return new possibilities
- If you have all permutations for N-1 and M, then you can use them to find the permutations for N and M by inserting e1 into them. You can't just insert everywhere though, because then you'll get duplicates. I don't know why this works, but you can calculate the number of new possibilities that you'll generate from an old one (I call this 'gain'). This number starts at M+1 for the first old permutation and decreases by one for each old permutation until it would become zero, at which point it goes back to M, etc. (only works if M>=N). So if you want to calculate the permutations for N=3 and M=3 and you have the 10 permutations for N=2 and M=3, their gains will be [4 3 2 1 3 2 1 2 1 1]. Subtract this gain from the length of the permutation and you get the index at which you can start inserting new elements without making duplicates.