991. Broken Calculator

On a broken calculator that has a number showing on its display, we can perform two operations:

• Double: Multiply the number on the display by 2, or;
• Decrement: Subtract 1 from the number on the display.

Initially, the calculator is displaying the number X.

Return the minimum number of operations needed to display the number Y.

Example 1:

Input: X = 2, Y = 3
Output: 2
Explanation: Use double operation and then decrement operation {2 -> 4 -> 3}.

Example 2:

Input: X = 5, Y = 8
Output: 2
Explanation: Use decrement and then double {5 -> 4 -> 8}.

Example 3:

Input: X = 3, Y = 10
Output: 3
Explanation:  Use double, decrement and double {3 -> 6 -> 5 -> 10}.

Example 4:

Input: X = 1024, Y = 1
Output: 1023
Explanation: Use decrement operations 1023 times.

Note:

1. 1 <= X <= 10^9
2. 1 <= Y <= 10^9

Approach #1: Math. [Java]

class Solution {
    public int brokenCalc(int x, int y) {
        int count = 0;
        while (y != x) {
            if (x > y) return x - y + count;

            if (y % 2 != 0) y += 1;
            else y /= 2;

            count++;
        }

        return count;
    }
}

　　

Analysis:

First, let us see if the solution exists or not.

Clearly, we can keep doubling x till it goes beyond y. Then we can keep decreamenting x till it reaches y. Since the number of operations is not limited, so we conclude that a solution exists.

So now, consider an optimal solution (any solution with the minimal number of steps).

The path is nothing but a sequence of numbers that start at x and end at y.

Assume (x <= y). The other case is trivial

Case 1) Y is odd

Now, consider the last second element of the sequence (optimal path). Recall that we can only move in the sequence via the allowed moves (in the forward direction, we multiply by 2 or decreament by 1). Let us back track and see which move did we actually use to get to y. (obviously it has to be one of the two moves).

Now, the move could not have been multiplication by 2, or else y would have been a multiple of 2, which violates our assumption. So the only possible move is the decrement move. It means that the last second term of the sequence is indeed y + 1 if y is odd. (And there is no other possibility).

So now we just need to compute the optimal length to reach y + 1, and then add 1 to our answer to get the optimal path length for y. (Why? It happens because y + 1 lies in an optimal path and any subpath of the optimal path must be optimal or else it would violates our assumptions).

Case 2) Y is even. Say, y = 2m

First, let us sudy the worst case analysis of what is the maximum number that you would touch if you play optimally.

Clearly it is 2 * (y - 1), since in the worst case, you may end up starting at y - 1 and jumping to 2 * (y - 1) and then coming back. In all other cases, the jump will lead you to a number less than 2 * (y - 1) and you can easily come back to y one step at a time.

Let us denote 2 * ( y - 1 ) as jump_max.

Now, if y is even, we cannot say anything about the last second term of the sequence. (The move could be either multiplication or decrement).

However, let us see what happens if the last move was multiplication by 2.

Clearly, the last second element in this case is y / 2 = m

So we need to compute the optimal path length to reach m and then we can add 1 to our answer. (But this is valid only if we know that the last move was indeed multiplication.)

what if the last move was decrement?

In that case, the last second element become 2m + 1, (odd number), and by the 1st lemma, we conclude that the last thrid number is 2m + 2.

Now 2m + 2 is an even number so either a jump happens or it's descendant is 2m + 4. So we keep going to the rigth untill we find ak such that 2m + 2k is obtained be jumping from m+k. Clearly such a number exists as the largest number we can encounter is jump_max.

So, now the path looks like:

x .......(m + k) -> 2 (m + k) -> (2m + 2k - 2) -> ...... y

But, if you observe carefully, after we reach (m + k) we can decrement k times to reach m and then double to get y. This would cost us (k+1) operations + the cost to reach (m + k). However, the current cost is (1 + 2 (m + k) - 2m) = (2k + 1) operations + the cost to reach (m+k). Since the new cost is lower, this violates our assumption that the original sequence was an optimal path. Therefore we have a contradiction and we conclude that the last move could not have been decrement.

Conclusion:

If y is odd, we know that the last number to be reached before y is (y + 1) (in the optimal path)

If y is even, we know that the last number to be reached before y is y / 2 (in the optimal path)

So finally we have recursive relation.

if (x >= y)

cost(x, y) = x - y

if (x < y)

cost(x, y) = 1 + cost(x, y+ 1) if y is odd

cost(x, y) = 1 + cost(x, y / 2) if y is even

This analysis may be easy to understand:

Trying to prove that if Y is even, the last operation must be doubling:

hypothesis: there can be one or more decrement from Y + 1 to Y in the shortest path, where last bit of Y is 0

since last bit of Y + 1 is 1, it must be decrement from Y + 2 (doubling can never make an 1 on last bit)

two options at Y + 2:

decrement from Y + 3, it's the same as the starting point Y + 1 and Y:

doubling from (Y+2)/2 three moves used from (Y+2)/2 to Y: double to Y + 2, decrement to Y+1, decrement to Y, while there is a shorter path: decrement to Y / 2, double to Y.

there we get a contradiction to the hypothesis

so the hypothesis is false

hence, there can be none decrement move(s) from Y + 1 to Y in the shortest path is last bit of Y is 0.

Reference:

https://leetcode.com/problems/broken-calculator/discuss/236565/Detailed-Proof-Of-Correctness-Greedy-Algorithm