# Posts published in “Greedy”

There are n different online courses numbered from 1 to n. Each course has some duration(course length) t and closed on dth day. A course should be taken continuouslyfor t days and must be finished before or on the dth day. You will start at the 1st day.

Given n online courses represented by pairs (t,d), your task is to find the maximal number of courses that can be taken.

Example:

Input: [[100, 200], [200, 1300], [1000, 1250], [2000, 3200]]
Output: 3
Explanation:
There're totally 4 courses, but you can take 3 courses at most:
First, take the 1st course, it costs 100 days so you will finish it on the 100th day, and ready to take the next course on the 101st day.
Second, take the 3rd course, it costs 1000 days so you will finish it on the 1100th day, and ready to take the next course on the 1101st day.
Third, take the 2nd course, it costs 200 days so you will finish it on the 1300th day.
The 4th course cannot be taken now, since you will finish it on the 3300th day, which exceeds the closed date.


Note:

1. The integer 1 <= d, t, n <= 10,000.
2. You can’t take two courses simultaneously.

## Solution: Priority queue

1. Sort courses by end date
2. Use a priority queue (Max-Heap) to store the course lengths or far
3. Swap with a longer course if we could not take the current one

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

## C++

N cars are going to the same destination along a one lane road.  The destination is target miles away.

Each car i has a constant speed speed[i] (in miles per hour), and initial position position[i] miles towards the target along the road.

A car can never pass another car ahead of it, but it can catch up to it, and drive bumper to bumper at the same speed.

The distance between these two cars is ignored – they are assumed to have the same position.

car fleet is some non-empty set of cars driving at the same position and same speed.  Note that a single car is also a car fleet.

If a car catches up to a car fleet right at the destination point, it will still be considered as one car fleet.

How many car fleets will arrive at the destination?

Example 1:

Input: target = 12, position = [10,8,0,5,3], speed = [2,4,1,1,3]
Output: 3
Explanation:
The cars starting at 10 and 8 become a fleet, meeting each other at 12.
The car starting at 0 doesn't catch up to any other car, so it is a fleet by itself.
The cars starting at 5 and 3 become a fleet, meeting each other at 6.
Note that no other cars meet these fleets before the destination, so the answer is 3.


Note:

1. 0 <= N <= 10 ^ 4
2. 0 < target <= 10 ^ 6
3. 0 < speed[i] <= 10 ^ 6
4. 0 <= position[i] < target
5. All initial positions are different.

## Solution: Greedy

1. Compute the time when each car can reach target.
2. Sort cars by position DESC

Answer will be number slow cars in the time array.

Ex 1:
target = 12
p = [10,8,0,5,3]
v = [2,4,1,1,3]

p     t
10    1  <- slow -- ^
8    1             |
5    7  <- slow -- ^
3    3             |
0   12  <- slow -- ^

Ex 2
target = 10
p = [5, 4, 3, 2, 1]
v = [1, 2, 3, 4, 5]

p     t
5     5  <- slow -- ^
4     3             |
3     2.33          |
2     2             |
1     1.8           |



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

## Python3

Given an array of non-negative integers, you are initially positioned at the first index of the array.

Each element in the array represents your maximum jump length at that position.

Your goal is to reach the last index in the minimum number of jumps.

Example:

Input: [2,3,1,1,4]
Output: 2
Explanation: The minimum number of jumps to reach the last index is 2.
Jump 1 step from index 0 to 1, then 3 steps to the last index.

Note:

You can assume that you can always reach the last index.

## Solution: Greedy

Jump as far as possible but lazily.

[2, 3, 1, 1, 4]
i    nums[i]   steps   near   far
-      -         0       0     0
0      2         0       0     2
1      3         1       2     4
2      1         1       2     4
3      1         2       4     4
4      4         2       4     8


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

## C++

Given an array A of integers, we must modify the array in the following way: we choose an i and replace A[i] with -A[i], and we repeat this process K times in total.  (We may choose the same index i multiple times.)

Return the largest possible sum of the array after modifying it in this way.

Example 1:

Input: A = [4,2,3], K = 1
Output: 5
Explanation: Choose indices (1,) and A becomes [4,-2,3].


Example 2:

Input: A = [3,-1,0,2], K = 3
Output: 6
Explanation: Choose indices (1, 2, 2) and A becomes [3,1,0,2].


Example 3:

Input: A = [2,-3,-1,5,-4], K = 2
Output: 13
Explanation: Choose indices (1, 4) and A becomes [2,3,-1,5,4].


Note:

1. 1 <= A.length <= 10000
2. 1 <= K <= 10000
3. -100 <= A[i] <= 100

## Solution: Sorting

Flip as many as negative numbers as possible, if K > # of negative numbers and K is odd, flip the smallest element in the array.

Time complexity: O(nlogn)
Space complexity: O(1)

## C++

In an array A containing only 0s and 1s, a K-bit flip consists of choosing a (contiguous) subarray of length K and simultaneously changing every 0 in the subarray to 1, and every 1 in the subarray to 0.

Return the minimum number of K-bit flips required so that there is no 0 in the array.  If it is not possible, return -1.

Example 1:

Input: A = [0,1,0], K = 1
Output: 2
Explanation: Flip A[0], then flip A[2].


Example 2:

Input: A = [1,1,0], K = 2
Output: -1
Explanation: No matter how we flip subarrays of size 2, we can't make the array become [1,1,1].


Example 3:

Input: A = [0,0,0,1,0,1,1,0], K = 3
Output: 3
Explanation:
Flip A[0],A[1],A[2]: A becomes [1,1,1,1,0,1,1,0]
Flip A[4],A[5],A[6]: A becomes [1,1,1,1,1,0,0,0]
Flip A[5],A[6],A[7]: A becomes [1,1,1,1,1,1,1,1]


Note:

1. 1 <= A.length <= 30000
2. 1 <= K <= A.length

## Solution: Greedy

From left most, if there is a 0, that bit must be flipped since the right ones won’t affect left ones.

Time complexity: O(nk) -> O(k)
Space complexity: O(1)

## C++ / O(n)

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