• [Swift]LeetCode1235.规划兼职工作 | Maximum Profit in Job Scheduling


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    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, you need to output the maximum profit you can take such that there are no 2 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

    Constraints:

    1 <= startTime.length == endTime.length == profit.length <= 5 * 10^4
    1 <= startTime[i] < endTime[i] <= 10^9
    1 <= profit[i] <= 10^4


    你打算利用空闲时间来做兼职工作赚些零花钱。

    这里有 n 份兼职工作,每份工作预计从 startTime[i] 开始到 endTime[i] 结束,报酬为 profit[i]。

    给你一份兼职工作表,包含开始时间 startTime,结束时间 endTime 和预计报酬 profit 三个数组,请你计算并返回可以获得的最大报酬。

    注意,时间上出现重叠的 2 份工作不能同时进行。

    如果你选择的工作在时间 X 结束,那么你可以立刻进行在时间 X 开始的下一份工作。 

    示例 1:

    输入:startTime = [1,2,3,3], endTime = [3,4,5,6], profit = [50,10,40,70]
    输出:120
    解释:
    我们选出第 1 份和第 4 份工作,
    时间范围是 [1-3]+[3-6],共获得报酬 120 = 50 + 70。
    示例 2:

    输入:startTime = [1,2,3,4,6], endTime = [3,5,10,6,9], profit = [20,20,100,70,60]
    输出:150
    解释:
    我们选择第 1,4,5 份工作。
    共获得报酬 150 = 20 + 70 + 60。
    示例 3:

    输入:startTime = [1,1,1], endTime = [2,3,4], profit = [5,6,4]
    输出:6

    提示:

    1 <= startTime.length == endTime.length == profit.length <= 5 * 10^4
    1 <= startTime[i] < endTime[i] <= 10^9
    1 <= profit[i] <= 10^4

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  • 原文地址:https://www.cnblogs.com/strengthen/p/11712815.html
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