# Posts tagged as “dp”

In a project, you have a list of required skills req_skills, and a list of people.  The i-th person people[i] contains a list of skills that person has.

Consider a sufficient team: a set of people such that for every required skill in req_skills, there is at least one person in the team who has that skill.  We can represent these teams by the index of each person: for example, team = [0, 1, 3] represents the people with skills people[0]people[1], and people[3].

Return any sufficient team of the smallest possible size, represented by the index of each person.

You may return the answer in any order.  It is guaranteed an answer exists.

Example 1:

Input: req_skills = ["java","nodejs","reactjs"], people = [["java"],["nodejs"],["nodejs","reactjs"]]
Output: [0,2]


Example 2:

Input: req_skills = ["algorithms","math","java","reactjs","csharp","aws"], people = [["algorithms","math","java"],["algorithms","math","reactjs"],["java","csharp","aws"],["reactjs","csharp"],["csharp","math"],["aws","java"]]
Output: [1,2]


Constraints:

• 1 <= req_skills.length <= 16
• 1 <= people.length <= 60
• 1 <= people[i].length, req_skills[i].length, people[i][j].length <= 16
• Elements of req_skills and people[i] are (respectively) distinct.
• req_skills[i][j], people[i][j][k] are lowercase English letters.
• It is guaranteed a sufficient team exists.

Solution: DP

## C++/HashTable

We have a sequence of books: the i-th book has thickness books[i][0] and height books[i][1].

We want to place these books in order onto bookcase shelves that have total width shelf_width.

We choose some of the books to place on this shelf (such that the sum of their thickness is <= shelf_width), then build another level of shelf of the bookcase so that the total height of the bookcase has increased by the maximum height of the books we just put down.  We repeat this process until there are no more books to place.

Note again that at each step of the above process, the order of the books we place is the same order as the given sequence of books.  For example, if we have an ordered list of 5 books, we might place the first and second book onto the first shelf, the third book on the second shelf, and the fourth and fifth book on the last shelf.

Return the minimum possible height that the total bookshelf can be after placing shelves in this manner.

Example 1:

Input: books = [[1,1],[2,3],[2,3],[1,1],[1,1],[1,1],[1,2]], shelf_width = 4
Output: 6
Explanation:
The sum of the heights of the 3 shelves are 1 + 3 + 2 = 6.
Notice that book number 2 does not have to be on the first shelf.


Constraints:

• 1 <= books.length <= 1000
• 1 <= books[i][0] <= shelf_width <= 1000
• 1 <= books[i][1] <= 1000

## Solution: DP

dp[i] := min height of placing books[0] ~ books[i]
dp[-1] = 0
dp[j] = min{dp[i-1] + max(h[i] ~ h[j])}, 0 < i <= j, sum(w[i] ~ w[j]) <= shelf_width

Time complexity: O(n^2)
Space complexity: O(n)

## C++

Given two strings str1 and str2, return the shortest string that has both str1 and str2 as subsequences.  If multiple answers exist, you may return any of them.

(A string S is a subsequence of string T if deleting some number of characters from T (possibly 0, and the characters are chosen anywherefrom T) results in the string S.)

Example 1:

Input: str1 = "abac", str2 = "cab"
Output: "cabac"
Explanation:
str1 = "abac" is a substring of "cabac" because we can delete the first "c".
str2 = "cab" is a substring of "cabac" because we can delete the last "ac".
The answer provided is the shortest such string that satisfies these properties.


Note:

1. 1 <= str1.length, str2.length <= 1000
2. str1 and str2 consist of lowercase English letters.

## Solution: LCS

Find the LCS (longest common sub-sequence) of two strings, and insert unmatched characters into the LCS.

Time complexity: O(mn)
Space complexity: O(mn)

## 1046. Last Stone Weight

Solution: Simulation (priority_queue)

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

## 1047. Remove All Adjacent Duplicates In String

Solution: Stack / Deque

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

## 1048. Longest String Chain

Solution: DP

dp[i] := max length of chain of (A[0] ~ A[i-1])

dp[i] = max{dp[j] + 1} if A[j] is prederrsor of A[i], 1 <= j <i

Time complexity: O(n^2*l)
Space complexity: O(n)

## 1049. Last Stone Weight II

Solution: DP / target sum

Time complexity: O(n * S) = O(n * 100)

Space complexity: O(S) = O(100)

## C++

iven two integer arrays A and B, return the maximum length of an subarray that appears in both arrays.

Example 1:

Input:
A: [1,2,3,2,1]
B: [3,2,1,4,7]
Output: 3
Explanation:
The repeated subarray with maximum length is [3, 2, 1].


Note:

1. 1 <= len(A), len(B) <= 1000
2. 0 <= A[i], B[i] < 100

## Solution: DP

dp[i][j] := max length of (A[0:i], B[0:j])

dp[i][j] = dp[i – 1][j – 1] + 1 if A[i-1] == B[j-1] else 0

Time complexity: O(m*n)
Space complexity: O(m*n) -> O(n)

## C++ S:O(min(m,n))

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