We have n
jobs, where every job is scheduled to be done from startTime[i]
to endTime[i]
, obtaining a profit of profit[i]
.
You‘re given the startTime
, endTime
and profit
arrays, return the maximum profit you can take such that there are no two jobs in the subset with overlapping time range.
If you choose a job that ends at time X
you will be able to start another job that starts at time X
.
Example 1:
Input: startTime = [1,2,3,3], endTime = [3,4,5,6], profit = [50,10,40,70] Output: 120 Explanation: The subset chosen is the first and fourth job. Time range [1-3]+[3-6] , we get profit of 120 = 50 + 70.
Example 2:
Input: startTime = [1,2,3,4,6], endTime = [3,5,10,6,9], profit = [20,20,100,70,60] Output: 150 Explanation: The subset chosen is the first, fourth and fifth job. Profit obtained 150 = 20 + 70 + 60.
Example 3:
Input: startTime = [1,1,1], endTime = [2,3,4], profit = [5,6,4] Output: 6
1 class Solution { 2 public int jobScheduling(int[] startTime, int[] endTime, int[] profit) { 3 int n = startTime.length; 4 int[][] jobs = new int[n][3]; 5 for (int i = 0; i < n; i++) { 6 jobs[i] = new int[] { startTime[i], endTime[i], profit[i] }; 7 } 8 Arrays.sort(jobs, (a, b) -> a[1] - b[1]); 9 TreeMap<Integer, Integer> dp = new TreeMap<>(); 10 dp.put(0, 0); 11 for (int[] job : jobs) { 12 int cur = dp.floorEntry(job[0]).getValue() + job[2]; 13 if (cur > dp.lastEntry().getValue()) 14 dp.put(job[1], cur); 15 } 16 return dp.lastEntry().getValue(); 17 } 18 }