Description
You are given a 0-indexed array of integers nums of length n. You are initially positioned at index 0.
Each element nums[i] represents the maximum length of a forward jump from index i. In other words, if you are at index i, you can jump to any index (i + j) where:
0 <= j <= nums[i]andi + j < n
Return the minimum number of jumps to reach index n - 1. The test cases are generated such that you can reach index n - 1.
Example 1:
Input: nums = [2,3,1,1,4] Output: 2 Explanation: The minimum number of jumps to reach the last index is 2. Jump 1 step from index 0 to 1, then 3 steps to the last index.
Example 2:
Input: nums = [2,3,0,1,4] Output: 2
Constraints:
1 <= nums.length <= 1040 <= nums[i] <= 1000- It's guaranteed that you can reach
nums[n - 1].
Solutions
Solution 1: Greedy Algorithm
We can use a variable mx to record the farthest position that can be reached from the current position, a variable last to record the position of the last jump, and a variable ans to record the number of jumps.
Next, we traverse each position i in [0,..n - 2]. For each position i, we can calculate the farthest position that can be reached from the current position through i + nums[i]. We use mx to record this farthest position, that is, mx = max(mx, i + nums[i]). Then, we check whether the current position has reached the boundary of the last jump, that is, i = last. If it has reached, then we need to make a jump, update last to mx, and increase the number of jumps ans by 1.
Finally, we return the number of jumps ans.
The time complexity is O(n), where n is the length of the array. The space complexity is O(1).
Similar problems:
class Solution: def jump(self, nums: List[int]) -> int: ans = mx = last = 0 for i, x in enumerate(nums[:-1]): mx = max(mx, i + x) if last == i: ans += 1 last = mx return ans(code-box)
