# Posts published in “Dynamic Programming”

You are given a 0-indexed 2D integer array tires where tires[i] = [fi, ri] indicates that the ith tire can finish its xth successive lap in fi * ri(x-1) seconds.

• For example, if fi = 3 and ri = 2, then the tire would finish its 1st lap in 3 seconds, its 2nd lap in 3 * 2 = 6 seconds, its 3rd lap in 3 * 22 = 12 seconds, etc.

You are also given an integer changeTime and an integer numLaps.

The race consists of numLaps laps and you may start the race with any tire. You have an unlimited supply of each tire and after every lap, you may change to any given tire (including the current tire type) if you wait changeTime seconds.

Return the minimum time to finish the race.

Example 1:

Input: tires = [[2,3],[3,4]], changeTime = 5, numLaps = 4
Output: 21
Explanation:
Lap 1: Start with tire 0 and finish the lap in 2 seconds.
Lap 2: Continue with tire 0 and finish the lap in 2 * 3 = 6 seconds.
Lap 3: Change tires to a new tire 0 for 5 seconds and then finish the lap in another 2 seconds.
Lap 4: Continue with tire 0 and finish the lap in 2 * 3 = 6 seconds.
Total time = 2 + 6 + 5 + 2 + 6 = 21 seconds.
The minimum time to complete the race is 21 seconds.


Example 2:

Input: tires = [[1,10],[2,2],[3,4]], changeTime = 6, numLaps = 5
Output: 25
Explanation:
Lap 1: Start with tire 1 and finish the lap in 2 seconds.
Lap 2: Continue with tire 1 and finish the lap in 2 * 2 = 4 seconds.
Lap 3: Change tires to a new tire 1 for 6 seconds and then finish the lap in another 2 seconds.
Lap 4: Continue with tire 1 and finish the lap in 2 * 2 = 4 seconds.
Lap 5: Change tires to tire 0 for 6 seconds then finish the lap in another 1 second.
Total time = 2 + 4 + 6 + 2 + 4 + 6 + 1 = 25 seconds.
The minimum time to complete the race is 25 seconds.


Constraints:

• 1 <= tires.length <= 105
• tires[i].length == 2
• 1 <= fi, changeTime <= 105
• 2 <= ri <= 105
• 1 <= numLaps <= 1000

## Solution: DP

Observation: since ri >= 2, we must change tire within 20 laps, otherwise it will be slower.

pre-compute the time to finish k laps using each type of tire (k < 20), find min for each lap.

dp[i] = best[i], i < 20,
dp[i] = min{dp[i – j] + changeTime + best[j]}, i > 20

Time complexity: O(n)
Space complexity: O(n) -> O(20)

## C++

You are given a 0-indexed 2D integer array questions where questions[i] = [pointsi, brainpoweri].

The array describes the questions of an exam, where you have to process the questions in order (i.e., starting from question 0) and make a decision whether to solve or skip each question. Solving question i will earn you pointsi points but you will be unable to solve each of the next brainpoweri questions. If you skip question i, you get to make the decision on the next question.

• For example, given questions = [[3, 2], [4, 3], [4, 4], [2, 5]]:
• If question 0 is solved, you will earn 3 points but you will be unable to solve questions 1 and 2.
• If instead, question 0 is skipped and question 1 is solved, you will earn 4 points but you will be unable to solve questions 2 and 3.

Return the maximum points you can earn for the exam.

Example 1:

Input: questions = [[3,2],[4,3],[4,4],[2,5]]
Output: 5
Explanation: The maximum points can be earned by solving questions 0 and 3.
- Solve question 0: Earn 3 points, will be unable to solve the next 2 questions
- Unable to solve questions 1 and 2
- Solve question 3: Earn 2 points
Total points earned: 3 + 2 = 5. There is no other way to earn 5 or more points.


Example 2:

Input: questions = [[1,1],[2,2],[3,3],[4,4],[5,5]]
Output: 7
Explanation: The maximum points can be earned by solving questions 1 and 4.
- Skip question 0
- Solve question 1: Earn 2 points, will be unable to solve the next 2 questions
- Unable to solve questions 2 and 3
- Solve question 4: Earn 5 points
Total points earned: 2 + 5 = 7. There is no other way to earn 7 or more points.


Constraints:

• 1 <= questions.length <= 105
• questions[i].length == 2
• 1 <= pointsi, brainpoweri <= 105

## Solution: DP

A more general version of 花花酱 LeetCode 198. House Robber

dp[i] := max points by solving questions[i:n].
dp[i] = max(dp[i + b + 1] + points[i] /* solve */ , dp[i+1] /* skip */)

ans = dp[0]

Time complexity: O(n)
Space complexity: O(n)

## Python3

You are given an integer array prices representing the daily price history of a stock, where prices[i] is the stock price on the ith day.

smooth descent period of a stock consists of one or more contiguous days such that the price on each day is lower than the price on the preceding day by exactly 1. The first day of the period is exempted from this rule.

Return the number of smooth descent periods.

Example 1:

Input: prices = [3,2,1,4]
Output: 7
Explanation: There are 7 smooth descent periods:
[3], [2], [1], [4], [3,2], [2,1], and [3,2,1]
Note that a period with one day is a smooth descent period by the definition.


Example 2:

Input: prices = [8,6,7,7]
Output: 4
Explanation: There are 4 smooth descent periods: [8], [6], [7], and [7]
Note that [8,6] is not a smooth descent period as 8 - 6 ≠ 1.


Example 3:

Input: prices = [1]
Output: 1
Explanation: There is 1 smooth descent period: [1]


Constraints:

• 1 <= prices.length <= 105
• 1 <= prices[i] <= 105

## Solution: DP

Same as longest decreasing subarray.

dp[i] := length of longest smoothing subarray ends with nums[i].

dp[i] = dp[i – 1] + 1 if nums[i] + 1 = nums[i – 1] else 1

Time complexity: O(n)
Space complexity: O(n) -> O(1)