Problem
Given a positive integer n
, find the smallest integer which has exactly the same digits existing in the integer n
and is greater in value than n
. If no such positive integer exists, return -1
.
Note that the returned integer should fit in 32-bit integer, if there is a valid answer but it does not fit in 32-bit integer, return -1
.
Examples
Example 1:
Input: n = 12
Output: 21
Example 2:
Input: n = 21
Output: -1
Example 3:
Input: n = 423862
Output: 426238
Here is a similar problem - Arrange Given Number To Form The Biggest Number Possible.
This is also similar code: Next Greater number with given set of digits
Solution
Method 1 - Greedy Approach
Lets look at example 3 - 423862.
- Go through each digit from right to left.
- Find the first digit that is not in descending order. In the example, it’s 3, 423862.
- For all digits after the current digit (862), find the smallest one that is also greater than the current digit, which is 6. Swap it with the current digit. ⇨ 423862
- So the current number is 426832.
- The last step is to sort all digits after the current digit (6) in ascending order, so we get 426238.
Code
public int nextGreaterElement(int n) {
char[] number = (n + "").toCharArray();
int i, j;
// I) Start from the right most digit and
// find the first digit that is
// smaller than the digit next to it.
for (i = number.length - 1; i > 0; i--) {
if (number[i - 1]<number[i]) {
break;
}
}
// If no such digit is found, its the edge case 1.
if (i == 0) {
return -1;
}
// II) Find the smallest digit on right side of (i-1)'th
// digit that is greater than number[i-1]
int x = number[i - 1], smallest = i;
for (j = i + 1; j<number.length; j++) {
if (number[j] > x && number[j]<= number[smallest]) {
smallest = j;
}
}
// III) Swap the above found smallest digit with
// number[i-1]
char temp = number[i - 1];
number[i - 1] = number[smallest];
number[smallest] = temp;
// IV) Sort the digits after (i-1) in ascending order
Arrays.sort(number, i, number.length);
long val = Long.parseLong(new String(number));
return (val<= Integer.MAX_VALUE) ? (int) val : -1;
}
Complexity
- ⏰ Time complexity:
O( log n)
wheren
is number of digits in number. - 🧺 Space complexity:
O(1)