Given a collection of numbers that might contain duplicates, return all possible unique permutations.
For example,
[1,1,2] have the following unique permutations:
[1,1,2], [1,2,1],
and [2,1,1].
generally finding all permutation will take N! time based on T(n) = n*T(n-1)
this approach we can trim some of the cases, example: num[i] == num[i-1] but we have not yet visit num[i - 1]
so it would be a little less than n! but still np
def backtrack(num, res, val, visit):
if len(val) == len(num) and :
res.append(val)
for i in range(len(num)):
if i > 0 and visit[i - 1] == False and num[i - 1] == num[i]:
continue
if visit[i] == False:
visit[i] = True
backtrack(num, res, val+[num[i]], visit)
visit[i] = False
def permuteUnique(num):
visit = [False for i in range(len(num))]
res = []
val = []
num.sort()
backtrack(num, res, val, visit)
return res
num = [1, 3, 1]
print permuteUnique(num)
本文探讨了如何在存在重复元素的情况下,找到所有独特的排列组合,通过使用回溯算法来减少不必要的计算,实现效率优化。
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