Description
A chef has collected data on the satisfaction
level of his n
dishes. Chef can cook any dish in 1 unit of time.
Like-time coefficient of a dish is defined as the time taken to cook that dish including previous dishes multiplied by its satisfaction level i.e. time[i] * satisfaction[i]
.
Return the maximum sum of like-time coefficient that the chef can obtain after dishes preparation.
Dishes can be prepared in any order and the chef can discard some dishes to get this maximum value.
Example 1:
Input: satisfaction = [-1,-8,0,5,-9] Output: 14 Explanation: After Removing the second and last dish, the maximum total like-time coefficient will be equal to (-1*1 + 0*2 + 5*3 = 14). Each dish is prepared in one unit of time.
Example 2:
Input: satisfaction = [4,3,2] Output: 20 Explanation: Dishes can be prepared in any order, (2*1 + 3*2 + 4*3 = 20)
Example 3:
Input: satisfaction = [-1,-4,-5] Output: 0 Explanation: People do not like the dishes. No dish is prepared.
Constraints:
n == satisfaction.length
1 <= n <= 500
-1000 <= satisfaction[i] <= 1000
Code
一開始寫的 解。但有直覺是 sort 過後要挑正的,至於負的就必須看加進去後和正的因為烹煮時間增加的 gain 誰比較大,將此想法 implement 後就是底下的 greedy 解法。
以 [-1,-8,0,5,-9]
為例, sort 過後是 [-9, -8, -1, 0, 5]
。
- iter 1: total = 5, ans = 5
- iter 2: total = 0 + 5, ans = 10
- iter 3: total = -1 + 0 + 5, ans = 14
- iter 4: total = -8 + -1 + 0 + 5 < 0
不斷地將 total 加到 ans 就是變相的在計算將比較好的 dish 延後烹煮順序進而得到的 gain。